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<a href="mma__tensor__op__tile__iterator_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION.  All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *     * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *       conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *     * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *       conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *       provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *     * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *       to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *       permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. 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href="memory__sm75_8h.html">cutlass/arch/memory_sm75.h</a>&quot;</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="include_2cutlass_2gemm_2gemm_8h.html">cutlass/gemm/gemm.h</a>&quot;</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="layout_2matrix_8h.html">cutlass/layout/matrix.h</a>&quot;</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tensor_8h.html">cutlass/layout/tensor.h</a>&quot;</span></div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="pitch__linear_8h.html">cutlass/layout/pitch_linear.h</a>&quot;</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tensor__op__multiplicand__sm75_8h.html">cutlass/layout/tensor_op_multiplicand_sm75.h</a>&quot;</span></div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="platform_8h.html">cutlass/platform/platform.h</a>&quot;</span></div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="fast__math_8h.html">cutlass/fast_math.h</a>&quot;</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="keyword">namespace </span>gemm {</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="keyword">namespace </span>warp {</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6">Operand</a> <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6">Operand</a>,</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keyword">typename</span> Layout_,</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordtype">int</span> Threads,</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    <span class="keywordtype">int</span> PartitionsK_ = 1&gt;</div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">   75</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    Operand Operand_,</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    <span class="keywordtype">int</span> PartitionsK_&gt;</div><div class="line"><a name="l00099"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html">   99</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">layout::TensorOpMultiplicandCongruous</a>&lt;sizeof_bits&lt;Element_&gt;::value,</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;                                                   64&gt;,</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a7ffcc9310bf82c2885e1e623e4a708aa">  107</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a7ffcc9310bf82c2885e1e623e4a708aa">Shape</a> = Shape_;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a530b17594e536bc6ddba532cf17dbc88">  110</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a> || kOperand== <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>,</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator may only be instantiated for A or B operands to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a06719b16473c4d23a4db597439199582">  116</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a06719b16473c4d23a4db597439199582">Element</a> = Element_;</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">cutlass::layout::TensorOpMultiplicandCongruous</a>&lt;</div><div class="line"><a name="l00120"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a15f54eea90d76efb8051333f883dd67c">  120</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, 64&gt;;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a2229636a51c6233ee4f9de8a0f15107a">  123</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a2229636a51c6233ee4f9de8a0f15107a">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a00bb713fb2ac605d69dc57014b058eb4">  126</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00129"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa50dce798dbb20fde71ba74627659cca">  129</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div><div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a40fe36af3b514a30200609a2e3b31dcd">  132</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsK = PartitionsK_;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a64e8723906c62ed8284a7c8e42627a4d">  135</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">  138</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a6f687d886a3e6eb106bfd59298e6f5c6">  141</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a6f687d886a3e6eb106bfd59298e6f5c6">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">  144</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html">  147</a></span>&#160;  <span class="keyword">struct </span>Policy {</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        !(Shape::kContiguous % InstructionShape::kContiguous),</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        <span class="stringliteral">&quot;Shape of warp-level Mma must be divisible by operator shape.&quot;</span>);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="comment">// Determine number of elements along outer dimension per individual LDSM op</span></div><div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#ab3627254bfb25506ae9f50d5793ddf08">  153</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kLdsmOpOuter = Layout::kElementsPerAccess;</div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#aecbe752f0ab6bd5d40885865e1c8136f">  154</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kLdsmOpInner = 8;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(!(Shape::kContiguous % kLdsmOpOuter),</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      <span class="stringliteral">&quot;Shape of warp-level mma must be divisible by LDSM&#39;s fundamental tile size.&quot;</span>);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(!(Shape::kStrided % kLdsmOpInner), </div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;      <span class="stringliteral">&quot;Shape of warp-level mma must be divisible by LDSM&#39;s fundamental tile size.&quot;</span>);</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#a8bb90a3c31441e3a45124b0a7feefa93">  163</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> LdsmShapeStrided =</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        InstructionShape::kStrided / kLdsmOpInner;</div><div class="line"><a name="l00165"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#a18e46ed2afcbd4e694dccb7dfbb42545">  165</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> LdsmShapeContiguous = 4 / LdsmShapeStrided;</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">LdsmShape</a> =</div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#a0008b4520085f127411ea8233de4b9db">  167</a></span>&#160;        <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape&lt;LdsmShapeContiguous, LdsmShapeStrided&gt;</a>;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">LdsmIterations</a> = <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape</a>&lt;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        Shape::kContiguous / Layout::kElementsPerAccess / LdsmShapeContiguous,</div><div class="line"><a name="l00172"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#a8672f4cac4739f8c6a1212d5260575d7">  172</a></span>&#160;        1&gt;;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___07638f8b7761f6e2e2e6918e2c05e739.html#ad8f1780a4422082360b148bd8d7ab279">  175</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kGroupsPerTile =</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        Shape::kStrided / InstructionShape::kStrided;</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  };</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOpDelta == 1,</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="stringliteral">&quot;Alternative arrangements not supported at present.&quot;</span>);</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPointerCount =</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;      Layout::TileShape::kContiguous / Policy::LdsmShape::kContiguous;</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  <span class="keyword">using</span> AccessType = Array&lt;Element, Layout::kElementsPerAccess&gt;;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="keywordtype">int</span> k_group_idx_;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div><div class="line"><a name="l00202"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">  202</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> = Array&lt;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a06719b16473c4d23a4db597439199582">Element</a>, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> stride_;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;  AccessType <span class="keyword">const</span> *pointer_[kPointerCount];</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> byte_offset_;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;  </div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aed04d00e3dd336bdfc9eff39e1123861">  219</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aed04d00e3dd336bdfc9eff39e1123861">MmaTensorOpMultiplicandTileIterator</a>(): stride_(0), byte_offset_(0) { }</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a14693f854e28e9f39e46843c5f805767">  223</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a14693f854e28e9f39e46843c5f805767">MmaTensorOpMultiplicandTileIterator</a>(</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  ):</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;    stride_(ref.stride(0) / <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">Layout</a>::kElementsPerAccess), byte_offset_(0),</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    k_group_idx_(0) {</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;      </div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    <span class="keywordtype">int</span> quad_pair = (lane_id &gt;&gt; 3);</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <span class="keywordtype">int</span> lane_in_quad = (lane_id &amp; 3);</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    <span class="keywordtype">int</span> lane_in_quad_pair = (lane_id &amp; 7);</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kPointerCount; ++i) {</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;      <span class="keywordtype">int</span> partition_contiguous_idx = -1;</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;      <span class="keywordtype">int</span> access_contiguous_idx = -1;</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;      <span class="keywordtype">int</span> access_strided_idx = -1;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      <span class="keywordflow">if</span> (Policy::LdsmShape::kContiguous == 4) {</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        partition_contiguous_idx = ((lane_in_quad_pair &gt;&gt; 2) ^ i);</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;        access_contiguous_idx = (quad_pair ^ lane_in_quad);</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        access_strided_idx = lane_in_quad_pair;</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;      }</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      <span class="keywordtype">int</span> access_contiguous =</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;          partition_contiguous_idx * Layout::PartitionShape::kContiguous +</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;          access_contiguous_idx;</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      <span class="keywordtype">int</span> access_strided = access_strided_idx;</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;      pointer_[i] = <span class="keyword">reinterpret_cast&lt;</span>AccessType <span class="keyword">const </span>*<span class="keyword">&gt;</span>(ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>()) +</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;                    access_contiguous + access_strided * stride_;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    }</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  }</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2bef766745fa8bfac1279a038b5bf23">  257</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2bef766745fa8bfac1279a038b5bf23">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a6f687d886a3e6eb106bfd59298e6f5c6">LongIndex</a> offset) {</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    byte_offset_ += offset * <span class="keyword">sizeof</span>(Element);</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;  }</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00266"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa061b3786066f1fbde3e6c993e2dec6c">  266</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa061b3786066f1fbde3e6c993e2dec6c">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    <span class="keywordtype">int</span> contiguous_offset = tile_offset.contiguous();</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <span class="keywordflow">if</span> (Shape::kContiguous ==</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        Layout::PartitionShape::kContiguous * Layout::kElementsPerAccess) {</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;      <span class="keywordflow">if</span> (tile_offset.contiguous() % 2) {</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kPointerCount / 2; ++i) {</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;          AccessType <span class="keyword">const</span> *tmp_pointer = pointer_[i];</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;          pointer_[i] = pointer_[i + kPointerCount / 2];</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;          pointer_[i + kPointerCount / 2] = tmp_pointer;</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        }</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;      }</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;      contiguous_offset = (tile_offset.contiguous() &gt;&gt; 1) &lt;&lt; 1;</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    }</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    <span class="keywordtype">int</span> offset = (tile_offset.strided() * InstructionShape::kStrided) *</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;                     stride_ * Layout::kElementsPerAccess +</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;                 contiguous_offset * Shape::kContiguous;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    add_pointer_offset(offset);</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  }</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00293"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9e8bb224bd9d307c1e8c7b0b898c3912">  293</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9e8bb224bd9d307c1e8c7b0b898c3912">operator++</a>() {</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;    add_tile_offset({0, 1});</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="keywordflow">if</span> (kPartitionsK &gt; 1) {</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;      ++k_group_idx_;</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;      <span class="comment">// Jump to next stage</span></div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;      <span class="keywordflow">if</span> (k_group_idx_ == Policy::kGroupsPerTile) {</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        k_group_idx_ = 0;</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        add_tile_offset(</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;            {0, ((kPartitionsK - 1) * Policy::kGroupsPerTile)});</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;      }</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    }</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;  }</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00312"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab273a94817606b8bdbc714a7964bd95b">  312</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab273a94817606b8bdbc714a7964bd95b">operator--</a>() {</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    byte_offset_ -= stride_ * InstructionShape::kStrided * <span class="keyword">sizeof</span>(Element) *</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;                    Layout::kElementsPerAccess;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;  }</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00321"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa711fab987df637da35e00d655dcaf65">  321</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa711fab987df637da35e00d655dcaf65">operator+=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    add_tile_offset(tile_offset);</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;  }</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a8da3cde971d4dd1beb123645b59e90db">  328</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a8da3cde971d4dd1beb123645b59e90db">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    add_tile_offset(-tile_offset);</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;  }</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00335"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1be13f61b06e0f27e27b0b54349cac5c">  335</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1be13f61b06e0f27e27b0b54349cac5c">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    load_with_byte_offset(frag, 0);</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;  }</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00342"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a15ab4cedbfb44dc89b7dcf69bdd9b5b4">  342</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a15ab4cedbfb44dc89b7dcf69bdd9b5b4">load_with_byte_offset</a>(</div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag,</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;    Array&lt;unsigned, Policy::LdsmShape::kCount&gt; *fetch_ptr = </div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;      <span class="keyword">reinterpret_cast&lt;</span>Array&lt;unsigned, Policy::LdsmShape::kCount&gt; *<span class="keyword">&gt;</span>(&amp;frag);</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> s = 0; s &lt; Policy::LdsmIterations::kStrided; ++s) {</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> c = 0; c &lt; Policy::LdsmIterations::kContiguous; ++c) {</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;        <span class="keywordtype">int</span> access_idx = c + s * Policy::LdsmIterations::kContiguous;</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;        AccessType <span class="keyword">const</span> *source_ptr =</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;            pointer_[c % kPointerCount] +</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;            Layout::TileShape::kContiguous * (c / kPointerCount) +</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;            Policy::LdsmShape::kStrided * s * stride_;</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        <span class="keywordtype">char</span> <span class="keyword">const</span> *source_byte_ptr = <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span> <span class="keyword">const </span>*<span class="keyword">&gt;</span>(source_ptr) + byte_offset + byte_offset_;</div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;        cutlass::arch::ldsm&lt;layout::ColumnMajor, Policy::LdsmShape::kCount&gt;(</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;          fetch_ptr[access_idx],</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;          source_byte_ptr</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;        );</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;      }</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;    }</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;  }</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;</div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00376"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9faeee6e6b7c8a8aaa0b60a47b93476b">  376</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9faeee6e6b7c8a8aaa0b60a47b93476b">load_with_pointer_offset</a>(</div><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag,</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;    load_with_byte_offset(frag, pointer_offset * <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;  }</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1e1b513870c418a8430cfecd56b60b98">  386</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1e1b513870c418a8430cfecd56b60b98">load</a>(</div><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag,</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    load_with_byte_offset(frag, tile_offset, 0);</div><div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;  }</div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;</div><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00396"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2fbe2cbd187897d82c4ad0de6cc6008">  396</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2fbe2cbd187897d82c4ad0de6cc6008">load</a>(</div><div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag,</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    load_with_byte_offset(frag, tile_offset, pointer_offset * <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;  }</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;</div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00408"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#af8c5a6fe57db046155a8145fe386dbc1">  408</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#af8c5a6fe57db046155a8145fe386dbc1">load_with_byte_offset</a>(</div><div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">Fragment</a> &amp;frag,</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">Index</a> pointer_offset = </div><div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;      tile_offset.contiguous() * Shape::kContiguous / Layout::kElementsPerAccess + </div><div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;      tile_offset.strided() * InstructionShape::kStrided * stride_;</div><div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;</div><div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;    byte_offset += <span class="keyword">sizeof</span>(AccessType) * pointer_offset;</div><div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;</div><div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;    load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;  }</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;</div><div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00432"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aafd0dda75aa9b12d787a8aca0e48c4df">  432</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aafd0dda75aa9b12d787a8aca0e48c4df">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <span class="comment">// no op</span></div><div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;  }</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;};</div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;</div><div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    Operand Operand_,</div><div 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name="l00459"></a><span class="lineno">  459</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCongruous.html">layout::ColumnMajorTensorOpMultiplicandCongruous</a>&lt;</div><div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;        sizeof_bits&lt;Element_&gt;::value, int(128 / sizeof(Element_))&gt;,</div><div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;</div><div class="line"><a name="l00466"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab240ac0cbcdf7d654f5c37fc0f726f65">  466</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab240ac0cbcdf7d654f5c37fc0f726f65">Shape</a> = Shape_;</div><div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;</div><div class="line"><a name="l00469"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a30e53857ae2e6c76b22780441871505c">  469</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;</div><div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a>,</div><div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;                <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator for ColumnMajor Congruous may &quot;</span></div><div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;                <span class="stringliteral">&quot;only be instantiated for A operand to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;</div><div class="line"><a name="l00476"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a052283230cbfb19fdc57482b12e91429">  476</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a052283230cbfb19fdc57482b12e91429">Element</a> = Element_;</div><div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCongruous.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCongruous.html">cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous</a>&lt;</div><div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae93f560012e11ed9d4aaad6dd0b3d2f1">  480</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, int(128 / <span class="keyword">sizeof</span>(Element_))&gt;;</div><div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;</div><div class="line"><a name="l00483"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa3eecd0ea10efc45a6c11569a3e9d1b5">  483</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa3eecd0ea10efc45a6c11569a3e9d1b5">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;</div><div class="line"><a name="l00486"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a4214c67c61ac0a06916ddde36fe67e10">  486</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;</div><div class="line"><a name="l00489"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a4b4676149ae60900c59b5aee37f32356">  489</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;</div><div class="line"><a name="l00492"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a548f06574ccccacdf1bb5d58f15a4249">  492</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;</div><div class="line"><a name="l00495"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">  495</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;</div><div class="line"><a name="l00498"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1d168c4b070f87a65bf900e7a63e14f3">  498</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1d168c4b070f87a65bf900e7a63e14f3">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;</div><div class="line"><a name="l00501"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">  501</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;</div><div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape&lt;Shape::kRow, Shape::kColumn&gt;</a>, kOperand, <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a052283230cbfb19fdc57482b12e91429">Element</a>,</div><div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">layout::TensorOpMultiplicandCongruous&lt;sizeof_bits&lt;Element_&gt;::value</a>,</div><div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;                                            int(128 / <span class="keyword">sizeof</span>(Element_))&gt;,</div><div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape</a>&lt;InstructionShape::kRow,</div><div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;                               InstructionShape::kColumn&gt;,</div><div class="line"><a name="l00510"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a8af5160e9f060dd3709a468ef82a3f81">  510</a></span>&#160;      kOpDelta, kThreads, PartitionsK_&gt;;</div><div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;</div><div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;</div><div class="line"><a name="l00519"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">  519</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;</div><div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;</div><div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> iterator_;</div><div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;</div><div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;  </div><div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00530"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab01cd5a33f54ab40ffea40556a042329">  530</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab01cd5a33f54ab40ffea40556a042329">MmaTensorOpMultiplicandTileIterator</a>() { }</div><div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;</div><div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00534"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab92dd8e4707aa642654935e4ab9c6ae7">  534</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab92dd8e4707aa642654935e4ab9c6ae7">MmaTensorOpMultiplicandTileIterator</a>(</div><div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;  ): iterator_({ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>(), ref.<a class="code" href="classcutlass_1_1TensorRef.html#a191e88bc0fb310be655d700e937ab97c">stride</a>()}, lane_id) {</div><div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;  }</div><div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;</div><div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00542"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae008d65b6f163052d6f261004964dfd7">  542</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae008d65b6f163052d6f261004964dfd7">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1d168c4b070f87a65bf900e7a63e14f3">LongIndex</a> offset) {</div><div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;</div><div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;    iterator_.add_pointer_offset(offset);</div><div 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href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a5b065c7d3bcc3ac6826e65dab9092bd3">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;</div><div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    iterator_.add_tile_offset({tile_offset.row(), tile_offset.column()});</div><div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;</div><div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;  }</div><div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;</div><div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00560"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aacfc1f7f194fad9371391134b2acf801">  560</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aacfc1f7f194fad9371391134b2acf801">operator++</a>() {</div><div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;</div><div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;    ++iterator_;</div><div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;</div><div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;  }</div><div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;</div><div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div 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class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;  }</div><div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;</div><div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00578"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aae859de5fea22c7ee1653d9eabe0468d">  578</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aae859de5fea22c7ee1653d9eabe0468d">operator+=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;    add_tile_offset(PitchLinearCoord(tile_offset.row(), tile_offset.column()));</div><div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;  }</div><div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;</div><div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00585"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a8379144007ec28f9b99ff85f255bed49">  585</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a8379144007ec28f9b99ff85f255bed49">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;    add_tile_offset(-PitchLinearCoord(tile_offset.row(), tile_offset.column()));</div><div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;  }</div><div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;</div><div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00592"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a3d83eeb065bda5634f6d739c1584bee0">  592</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a3d83eeb065bda5634f6d739c1584bee0">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;</div><div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;    iterator_.load(frag);</div><div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;  }</div><div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;</div><div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00599"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1a46c311062f11a9eb5a4f34407f022b">  599</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1a46c311062f11a9eb5a4f34407f022b">load_with_pointer_offset</a>(</div><div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag,</div><div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;    iterator_.load_with_pointer_offset(frag, pointer_offset);</div><div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;  }</div><div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;</div><div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00609"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a6ebdb3095e18ac34da6e7947fc050d26">  609</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a6ebdb3095e18ac34da6e7947fc050d26">load_with_byte_offset</a>(</div><div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag,</div><div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;    iterator_.load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;  }</div><div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;</div><div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00619"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a5f71a3fd5d0ee7ecf6ab1278b21e0574">  619</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a5f71a3fd5d0ee7ecf6ab1278b21e0574">load</a>(</div><div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag,</div><div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;  }</div><div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;</div><div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00629"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa8b7ca3aa65707a67da0f1e1f9abc6bf">  629</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa8b7ca3aa65707a67da0f1e1f9abc6bf">load</a>(</div><div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag,</div><div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;  }</div><div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;</div><div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00641"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7a6014e499e20aa8f4134c0dded53d09">  641</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7a6014e499e20aa8f4134c0dded53d09">load_with_byte_offset</a>(</div><div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">Fragment</a> &amp;frag,</div><div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;    iterator_.load_with_byte_offset(</div><div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;      frag,</div><div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;      {tile_offset.contiguous(), tile_offset.strided()},</div><div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;      byte_offset);</div><div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;  }</div><div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;</div><div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00662"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae7697f2e94df8d38463f136887d77533">  662</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae7697f2e94df8d38463f136887d77533">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;    iterator_.set_kgroup_index(k_group); </div><div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;  }</div><div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;};</div><div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;</div><div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;</div><div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;    Operand Operand_,</div><div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;    <span class="keywordtype">int</span> PartitionsK_&gt;</div><div class="line"><a name="l00689"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html">  689</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCongruous.html">layout::RowMajorTensorOpMultiplicandCongruous</a>&lt;</div><div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;        sizeof_bits&lt;Element_&gt;::value, int(128 / sizeof(Element_))&gt;,</div><div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;</div><div class="line"><a name="l00697"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a332174db47ba7103e8165861b1383b4a">  697</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a332174db47ba7103e8165861b1383b4a">Shape</a> = Shape_;</div><div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;</div><div class="line"><a name="l00700"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aae1f7b3b5fe4c031fbd323536af102ac">  700</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;</div><div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>,</div><div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;                <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator for RowMajor Congruous may &quot;</span></div><div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;                <span class="stringliteral">&quot;only be instantiated for B operand to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;</div><div class="line"><a name="l00707"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a461ec8799dc124e39b56e78d1d7b2501">  707</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;</div><div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCongruous.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCongruous.html">cutlass::layout::RowMajorTensorOpMultiplicandCongruous</a>&lt;</div><div class="line"><a name="l00711"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab2818c6132241f008d412a47e5b65e76">  711</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, int(128 / <span class="keyword">sizeof</span>(Element_))&gt;;</div><div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;</div><div class="line"><a name="l00714"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad91c3ff6512ec6f63dac11af36f553cb">  714</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad91c3ff6512ec6f63dac11af36f553cb">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;</div><div class="line"><a name="l00717"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a9debc539c23e32863ce5ba1ca39226bb">  717</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;</div><div class="line"><a name="l00720"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a4e504f50ad5b8106d8f26abdf2c77eed">  720</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;</div><div class="line"><a name="l00723"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aa9b319d97a8bfe2f51c78c8e3a2ad77d">  723</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;</div><div class="line"><a name="l00726"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">  726</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;</div><div class="line"><a name="l00729"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a86cfe634c08dbf97d12b62eeaff1fa2c">  729</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a86cfe634c08dbf97d12b62eeaff1fa2c">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;</div><div class="line"><a name="l00732"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">  732</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;</div><div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape&lt;Shape::kColumn, Shape::kRow&gt;</a>, kOperand, Element,</div><div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160;      layout::TensorOpMultiplicandCongruous&lt;sizeof_bits&lt;Element_&gt;::value,</div><div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160;                                            int(128 / <span class="keyword">sizeof</span>(Element_))&gt;,</div><div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape</a>&lt;InstructionShape::kColumn,</div><div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;                               InstructionShape::kRow&gt;,</div><div class="line"><a name="l00741"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ae9d2a2b4d378e778e1ca6b60d96aa250">  741</a></span>&#160;      kOpDelta, kThreads, PartitionsK_&gt;;</div><div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;</div><div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;</div><div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;</div><div class="line"><a name="l00750"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">  750</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;</div><div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;</div><div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> iterator_;</div><div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;</div><div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;  </div><div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00761"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a459d61e80b72846e8a096b5c93e3b7a8">  761</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a459d61e80b72846e8a096b5c93e3b7a8">MmaTensorOpMultiplicandTileIterator</a>() { }</div><div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;</div><div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00765"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a2f1d8841e730498582a557e73c1467fe">  765</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a2f1d8841e730498582a557e73c1467fe">MmaTensorOpMultiplicandTileIterator</a>(</div><div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;  ): iterator_({ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>(), ref.<a class="code" href="classcutlass_1_1TensorRef.html#a191e88bc0fb310be655d700e937ab97c">stride</a>()}, lane_id) {</div><div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;  }</div><div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;</div><div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00773"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab49df5f2b62c1dbc7533d1ad36881d5c">  773</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab49df5f2b62c1dbc7533d1ad36881d5c">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a86cfe634c08dbf97d12b62eeaff1fa2c">LongIndex</a> offset) {</div><div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;</div><div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;    iterator_.add_pointer_offset(offset);</div><div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;</div><div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;  }</div><div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;</div><div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00782"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#af05eb3e5ea74cdeadfeda004b42ce8a1">  782</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#af05eb3e5ea74cdeadfeda004b42ce8a1">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;</div><div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;    iterator_.add_tile_offset({tile_offset.column(), tile_offset.row()});</div><div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;</div><div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;  }</div><div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;</div><div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00791"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#acce80cd5cb5ab6c23795a8748c427610">  791</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#acce80cd5cb5ab6c23795a8748c427610">operator++</a>() {</div><div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;</div><div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;    ++iterator_;</div><div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;</div><div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div 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812</span>&#160;  }</div><div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;</div><div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00816"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad0e1edd1608df393c451b9ac6bd079de">  816</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad0e1edd1608df393c451b9ac6bd079de">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;    add_tile_offset(-PitchLinearCoord(tile_offset.column(), tile_offset.row()));</div><div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;  }</div><div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;</div><div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l00823"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ae6d98630ac77ae55f55281d7a9055b66">  823</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ae6d98630ac77ae55f55281d7a9055b66">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;</div><div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;    iterator_.load(frag);</div><div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160;  }</div><div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;</div><div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00830"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a6c481c9a25374ae10fc47e17d5736b89">  830</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a6c481c9a25374ae10fc47e17d5736b89">load_with_pointer_offset</a>(</div><div class="line"><a name="l00832"></a><span class="lineno">  832</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag,</div><div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;    iterator_.load_with_pointer_offset(frag, pointer_offset);</div><div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160;  }</div><div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;</div><div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00840"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a790515ce517729945be3a05828ca5882">  840</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a790515ce517729945be3a05828ca5882">load_with_byte_offset</a>(</div><div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag,</div><div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;    iterator_.load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;  }</div><div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;</div><div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00850"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a4837610efc606b2c8103f8271faad178">  850</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a4837610efc606b2c8103f8271faad178">load</a>(</div><div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag,</div><div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;  }</div><div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;</div><div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00860"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad44b3c1bfee9f5a8ddc962e78d81aefb">  860</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad44b3c1bfee9f5a8ddc962e78d81aefb">load</a>(</div><div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag,</div><div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;  }</div><div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;</div><div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00872"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aaf694dd4b0520ff3430a012777f350bc">  872</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aaf694dd4b0520ff3430a012777f350bc">load_with_byte_offset</a>(</div><div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">Fragment</a> &amp;frag,</div><div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;    iterator_.load_with_byte_offset(</div><div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;      frag,</div><div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;      {tile_offset.strided(), tile_offset.contiguous()},</div><div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;      byte_offset);</div><div class="line"><a name="l00883"></a><span class="lineno">  883</span>&#160;  }</div><div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;</div><div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l00893"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aacb661cde511fb812d82d0490c936195">  893</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aacb661cde511fb812d82d0490c936195">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;    iterator_.set_kgroup_index(k_group); </div><div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;  }</div><div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;};</div><div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;</div><div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;</div><div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00909"></a><span class="lineno">  909</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l00911"></a><span class="lineno">  911</span>&#160;    Operand Operand_,</div><div class="line"><a name="l00913"></a><span class="lineno">  913</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l00915"></a><span class="lineno">  915</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l00918"></a><span class="lineno">  918</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l00920"></a><span class="lineno">  920</span>&#160;    <span class="keywordtype">int</span> Crosswise,</div><div class="line"><a name="l00922"></a><span class="lineno">  922</span>&#160;    <span class="keywordtype">int</span> PartitionsK_&gt;</div><div class="line"><a name="l00923"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html">  923</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l00924"></a><span class="lineno">  924</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l00925"></a><span class="lineno">  925</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">layout::TensorOpMultiplicandCrosswise</a>&lt;sizeof_bits&lt;Element_&gt;::value,</div><div class="line"><a name="l00926"></a><span class="lineno">  926</span>&#160;                                                   Crosswise&gt;,</div><div class="line"><a name="l00927"></a><span class="lineno">  927</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l00928"></a><span class="lineno">  928</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00930"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a847a66cca3fbafbd3d4cce72a9ad2440">  930</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a847a66cca3fbafbd3d4cce72a9ad2440">Shape</a> = Shape_;</div><div class="line"><a name="l00931"></a><span class="lineno">  931</span>&#160;</div><div class="line"><a name="l00933"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a4a21ce52fa53c0e49926df3bc2ceb68b">  933</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;</div><div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a> || kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>,</div><div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;                <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator may only be instantiated for &quot;</span></div><div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;                <span class="stringliteral">&quot;A or B operands to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160;</div><div class="line"><a name="l00940"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a917f156978028a6cda77674086f67c3e">  940</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;</div><div class="line"><a name="l00943"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#acc6388e433c480e8316fb1e628f13e0c">  943</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kCrosswise = Crosswise;</div><div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;</div><div class="line"><a name="l00946"></a><span class="lineno">  946</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">cutlass::layout::TensorOpMultiplicandCrosswise</a>&lt;</div><div class="line"><a name="l00947"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2f70d5b508aa97478efb818412f385ff">  947</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, kCrosswise&gt;;</div><div class="line"><a name="l00948"></a><span class="lineno">  948</span>&#160;</div><div class="line"><a name="l00950"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a276c1d33c1380292ac581eae6afe00f2">  950</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a276c1d33c1380292ac581eae6afe00f2">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l00951"></a><span class="lineno">  951</span>&#160;</div><div class="line"><a name="l00954"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a702ec66954f8e450236d4db5b59f425a">  954</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l00955"></a><span class="lineno">  955</span>&#160;</div><div class="line"><a name="l00957"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a9c503e45168ab6d5f770520e29d61c98">  957</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l00958"></a><span class="lineno">  958</span>&#160;</div><div class="line"><a name="l00960"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#afb13a3b770bb8bb8ddb3db23a83489ed">  960</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsK = PartitionsK_;</div><div class="line"><a name="l00961"></a><span class="lineno">  961</span>&#160;</div><div class="line"><a name="l00963"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a850457c90597a384939b590604ca4edf">  963</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l00964"></a><span class="lineno">  964</span>&#160;</div><div class="line"><a name="l00966"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">  966</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l00967"></a><span class="lineno">  967</span>&#160;</div><div class="line"><a name="l00969"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab4334bc63da845c9606103e04f389a6d">  969</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab4334bc63da845c9606103e04f389a6d">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l00970"></a><span class="lineno">  970</span>&#160;</div><div class="line"><a name="l00972"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">  972</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l00973"></a><span class="lineno">  973</span>&#160;</div><div class="line"><a name="l00975"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0784c74bd670999ec23ad8ef9dc55777.html">  975</a></span>&#160;  <span class="keyword">struct </span>Policy {</div><div class="line"><a name="l00976"></a><span class="lineno">  976</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00977"></a><span class="lineno">  977</span>&#160;        !(Shape::kContiguous % InstructionShape::kContiguous),</div><div class="line"><a name="l00978"></a><span class="lineno">  978</span>&#160;        <span class="stringliteral">&quot;Shape of warp-level Mma must be divisible by operator shape.&quot;</span>);</div><div class="line"><a name="l00979"></a><span class="lineno">  979</span>&#160;</div><div class="line"><a name="l00980"></a><span class="lineno">  980</span>&#160;    <span class="comment">// Determine number of elements along outer dimension per individual LDSM op</span></div><div class="line"><a name="l00981"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0784c74bd670999ec23ad8ef9dc55777.html#a069db210d212589ef01cc0ad1d69ee65">  981</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kLdsmOpOuter = Layout::kElementsPerAccess;</div><div class="line"><a name="l00982"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0784c74bd670999ec23ad8ef9dc55777.html#a1590e539d3eb1072f78c653cae1d73d0">  982</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kLdsmOpInner = 8;</div><div class="line"><a name="l00983"></a><span class="lineno">  983</span>&#160;</div><div class="line"><a name="l00984"></a><span class="lineno">  984</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(!(Shape::kContiguous % kLdsmOpOuter),</div><div class="line"><a name="l00985"></a><span class="lineno">  985</span>&#160;                  <span class="stringliteral">&quot;Shape of warp-level mma must be divisible by LDSM&#39;s &quot;</span></div><div class="line"><a name="l00986"></a><span class="lineno">  986</span>&#160;                  <span class="stringliteral">&quot;fundamental tile size.&quot;</span>);</div><div class="line"><a name="l00987"></a><span class="lineno">  987</span>&#160;</div><div class="line"><a name="l00988"></a><span class="lineno">  988</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(!(Shape::kStrided % kLdsmOpInner),</div><div class="line"><a name="l00989"></a><span class="lineno">  989</span>&#160;                  <span class="stringliteral">&quot;Shape of warp-level mma must be divisible by LDSM&#39;s &quot;</span></div><div class="line"><a name="l00990"></a><span class="lineno">  990</span>&#160;                  <span class="stringliteral">&quot;fundamental tile size.&quot;</span>);</div><div class="line"><a name="l00991"></a><span class="lineno">  991</span>&#160;</div><div class="line"><a name="l00993"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0784c74bd670999ec23ad8ef9dc55777.html#ae65742246163ec6c911f4d153beecfe6">  993</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> LdsmShapeContiguous =</div><div class="line"><a name="l00994"></a><span class="lineno">  994</span>&#160;        InstructionShape::kContiguous / kLdsmOpOuter;</div><div class="line"><a name="l00995"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0784c74bd670999ec23ad8ef9dc55777.html#a4e3960dcef4ce7298df62cbf64a4f7d1">  995</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> LdsmShapeStrided =</div><div class="line"><a name="l00996"></a><span class="lineno">  996</span>&#160;        ((4 / LdsmShapeContiguous * kLdsmOpInner) &gt; Shape::kStrided)</div><div class="line"><a name="l00997"></a><span class="lineno">  997</span>&#160;            ? 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                                     Layout::kFactor / LdsmShape::kContiguous;</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160;  };</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160;</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOpDelta == 1,</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>&#160;                <span class="stringliteral">&quot;Alternative arrangements not supported at present.&quot;</span>);</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>&#160;</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>&#160;  <span class="keyword">using</span> AccessType = Array&lt;Element, Layout::kElementsPerAccess&gt;;</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160;</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160;</div><div class="line"><a name="l01026"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb"> 1026</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160;</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160;</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;  <span class="keywordtype">int</span> sections_;</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160;</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> stride_;</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160;</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160;  AccessType <span class="keyword">const</span> *pointer_;</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160;</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> byte_offset_;</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160;</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160;  <span class="keywordtype">int</span> k_group_idx_;</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160;</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01052"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab12387376473d0975cbf02f9d04a153c"> 1052</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab12387376473d0975cbf02f9d04a153c">MmaTensorOpMultiplicandTileIterator</a>()</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160;      : pointer_(<a class="code" href="platform_8h.html#ab979d9d4b4923f7c54d6caa6e1a61936">nullptr</a>),</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160;        sections_(0),</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160;        stride_(0),</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160;        byte_offset_(0),</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160;        k_group_idx_(0) {}</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160;</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160; 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       <span class="comment">// stride_ = kCrosswise x sections_ x kFactor</span></div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160;        stride_(ref.stride(0) * <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">Layout</a>::kFactor / <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">Layout</a>::kElementsPerAccess),</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160;        byte_offset_(0),</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160;        k_group_idx_(0) {</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;    <span class="comment">// Warp level iterator at most use double buffer to hide latency.  If there</span></div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160;    <span class="comment">// are more than 2 sections, every stage should have more than 1 section.</span></div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;    <span class="comment">// TODO: refactor code after every case is implemented</span></div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160;</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;    <span class="comment">// Turing silicon requires all 32 threads in a warp provide valid addresses</span></div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;    <span class="comment">// even for LDSM.1 and LDSM.2</span></div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160;<span class="preprocessor">#if (defined(__CUDA_ARCH__) &amp;&amp; (__CUDA_ARCH__ == 750))</span></div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;    lane_id = lane_id % (Policy::LdsmShape::kCount * Policy::kLdsmOpInner);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;    <span class="keywordtype">int</span> lane_in_pair = (lane_id &amp; 1);</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;    <span class="keywordtype">int</span> lane_in_quad = (lane_id &amp; 3);</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160;    <span class="keywordtype">int</span> lane_in_quad_pair = (lane_id &amp; 7);</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160;    <span class="keywordtype">int</span> lane_in_quad_quad = (lane_id &amp; 15);</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160;</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160;    <span class="keywordtype">int</span> partition_contiguous_idx = -1;</div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160;    <span class="keywordtype">int</span> access_contiguous_idx = -1;</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160;    <span class="keywordtype">int</span> access_strided_idx = -1;</div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160;</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160;    <span class="keywordflow">if</span> (Layout::kFactor == 4) {</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>&#160;      <span class="comment">// Super Integer matrix multiply Interleaved-32</span></div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>&#160;</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>&#160;      <span class="keywordtype">int</span> factor_in_partition =</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160;          (Layout::PartitionShape::kContiguous * Layout::kFactor /</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>&#160;           Layout::TileShape::kContiguous);</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160;</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160;      <span class="keywordflow">if</span> (Policy::LdsmShape::kStrided == Policy::LdsmShape::kCount) {</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160;        <span class="comment">// Integer matrix multiply 8816  A/B</span></div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160;        partition_contiguous_idx = lane_in_quad / factor_in_partition;</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160;        access_contiguous_idx = ((lane_in_pair * factor_in_partition) ^</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160;                                 (lane_in_quad_quad / Layout::kFactor));</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160;        access_strided_idx = lane_id / Layout::kFactor;</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160;      }</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160;    } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (Layout::kFactor == 2) {</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160;      <span class="comment">// Super Matrix multiply kBlock = 32</span></div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160;      <span class="keywordflow">if</span> (Policy::LdsmShape::kStrided == Policy::LdsmShape::kCount) {</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>&#160;        <span class="comment">// (Q stands for 1 8x128bit block).</span></div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>&#160;        <span class="comment">// Q0</span></div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>&#160;        <span class="comment">// Q1</span></div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>&#160;        <span class="comment">// Q2</span></div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>&#160;        <span class="comment">// Q3</span></div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>&#160;        <span class="comment">// Four blocks are next to each other in the strided dimension.</span></div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>&#160;        partition_contiguous_idx = (lane_id % Layout::kFactor);</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>&#160;        access_contiguous_idx = (lane_in_quad_pair / Layout::kFactor);</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>&#160;        access_strided_idx = lane_id / Layout::kFactor;</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>&#160;      }</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>&#160;    } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (Layout::kFactor == 1) {</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>&#160;      <span class="comment">// Super Matrix multiply kBlock = 64</span></div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>&#160;      <span class="keywordflow">if</span> (Policy::LdsmShape::kStrided == Policy::LdsmShape::kCount) {</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>&#160;        <span class="comment">// Q0</span></div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>&#160;        <span class="comment">// Q1</span></div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>&#160;        <span class="comment">// Q2</span></div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>&#160;        <span class="comment">// Q3</span></div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>&#160;        partition_contiguous_idx = (lane_in_quad_pair &gt;&gt; 2);</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>&#160;        access_contiguous_idx = lane_in_quad;</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>&#160;        access_strided_idx = lane_id;</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>&#160;      }</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>&#160;    }</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160;</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160;    <span class="keywordtype">int</span> access_contiguous =</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160;        partition_contiguous_idx * Layout::PartitionShape::kContiguous +</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160;        access_contiguous_idx;</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160;</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>&#160;    <span class="keywordtype">int</span> access_strided = access_strided_idx;</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>&#160;</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>&#160;    byte_offset_ = (access_contiguous + access_strided * stride_) *</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>&#160;                   <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> * Layout::kElementsPerAccess / 8;</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>&#160;  }</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>&#160;</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01139"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a5729ea6986033389dae3e6a724292507"> 1139</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a5729ea6986033389dae3e6a724292507">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab4334bc63da845c9606103e04f389a6d">LongIndex</a> offset) {</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>&#160;    byte_offset_ += offset * <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> / 8;</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>&#160;</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>&#160;  }</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>&#160;</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01148"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a80210fe006f6058886d8aa53677af116"> 1148</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a80210fe006f6058886d8aa53677af116">add_tile_offset</a>(</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>&#160;    <span class="keywordtype">int</span> whole_tiles = tile_offset.contiguous() / Policy::kGroupsPerTile;</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>&#160;    <span class="keywordtype">int</span> k_groups_delta = tile_offset.contiguous() % Policy::kGroupsPerTile;</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>&#160;</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>&#160;    byte_offset_ ^= k_groups_delta * <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> *</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>&#160;                    Layout::kElementsPerAccess / 8;</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>&#160;    pointer_ +=</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>&#160;        tile_offset.strided() * stride_ * Shape::kStrided / Layout::kFactor +</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>&#160;        whole_tiles * stride_ / sections_;</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>&#160;  }</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>&#160;</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01163"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ae4af2d212abc11a8cf1a97d47b230f00"> 1163</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ae4af2d212abc11a8cf1a97d47b230f00">operator++</a>() {</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>&#160;</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>&#160;    <span class="comment">// Integer matrix multiply 8816  Interleaved-32</span></div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>&#160;    <span class="comment">//   ^1 ^1</span></div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>&#160;    <span class="comment">// Matrix multiply 1688 kblock=32 || Integer matrix multiply 8816 kblock=64</span></div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>&#160;    <span class="comment">//   ^1 ^3 ^1 ^3</span></div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>&#160;    <span class="comment">// Matrix multiply 1688 kblock=64</span></div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>&#160;    <span class="comment">//   ^1 ^3 ^1 ^7 ^1 ^3 ^1 ^7</span></div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>&#160;    <span class="keywordflow">if</span> ((Policy::kGroupsPerTile / kPartitionsK) &gt; 1) {</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>&#160;      <span class="keywordtype">int</span> mask = ((Policy::kGroupsPerTile / kPartitionsK) == 8)</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>&#160;                     ? 3</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>&#160;                     : (((Policy::kGroupsPerTile / kPartitionsK) == 4) ? 1 : 0);</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>&#160;</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>&#160;      <span class="keywordflow">if</span> (((k_group_idx_ &amp; mask) % 2) == 0)</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>&#160;        byte_offset_ ^= 1 * Policy::LdsmShape::kContiguous *</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>&#160;                        <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> *</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>&#160;                        Layout::kElementsPerAccess / 8;</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((k_group_idx_ &amp; mask) == 1)</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>&#160;        byte_offset_ ^= 3 * Policy::LdsmShape::kContiguous *</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>&#160;                        <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> *</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>&#160;                        Layout::kElementsPerAccess / 8;</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>&#160;      <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((k_group_idx_ &amp; mask) == 3)</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>&#160;        byte_offset_ ^= 7 * Policy::LdsmShape::kContiguous *</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>&#160;                        <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element&gt;::value</a> *</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>&#160;                        Layout::kElementsPerAccess / 8;</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>&#160;    }</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>&#160;</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>&#160;    k_group_idx_++;</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>&#160;</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>&#160;    <span class="keywordflow">if</span> (k_group_idx_ == (Policy::kGroupsPerTile / kPartitionsK)) {</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>&#160;      k_group_idx_ = 0;</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>&#160;      add_tile_offset({Policy::kGroupsPerTile, 0});</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>&#160;    }</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>&#160;</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>&#160;  }</div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>&#160;</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01202"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#af02b9089644245ee0d7cd4fab17b2026"> 1202</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#af02b9089644245ee0d7cd4fab17b2026">operator--</a>() { assert(0); }</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>&#160;</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01207"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a7407a4b2ac07e96c39c1e53aeb76a594"> 1207</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a7407a4b2ac07e96c39c1e53aeb76a594">operator+=</a>(</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>&#160;    add_tile_offset(tile_offset);</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>&#160;  }</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>&#160;</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01216"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a97d09b2ad300996739ff4d1935804aaa"> 1216</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a97d09b2ad300996739ff4d1935804aaa">operator-=</a>(</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>&#160;    add_tile_offset(-tile_offset);</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>&#160;  }</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>&#160;</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01224"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a33b7e2083273b6ecaacf7a98045e5ad7"> 1224</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a33b7e2083273b6ecaacf7a98045e5ad7">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag)<span class="keyword"> const </span>{ load_with_byte_offset(frag, 0); }</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>&#160;</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01228"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aa851acf5c1e2a7ffa24526eebb347c1f"> 1228</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aa851acf5c1e2a7ffa24526eebb347c1f">load_with_byte_offset</a>(</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag,</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>&#160;    Array&lt;unsigned, Policy::LdsmShape::kCount&gt; *fetch_ptr =</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>&#160;        <span class="keyword">reinterpret_cast&lt;</span>Array&lt;unsigned, Policy::LdsmShape::kCount&gt; *<span class="keyword">&gt;</span>(&amp;frag);</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>&#160;</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> s = 0; s &lt; Policy::LdsmIterations::kStrided; ++s) {</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> c = 0; c &lt; Policy::LdsmIterations::kContiguous; ++c) {</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>&#160;        <span class="keywordtype">int</span> access_idx = c + s * Policy::LdsmIterations::kContiguous;</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>&#160;</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>&#160;        AccessType <span class="keyword">const</span> *source_ptr =</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>&#160;            pointer_ + Policy::LdsmShape::kContiguous * c +</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>&#160;            Policy::kLdsmOpInner / Layout::kFactor *</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>&#160;                Policy::LdsmShape::kStrided * s * stride_;</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>&#160;</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>&#160;        <span class="keywordtype">char</span> <span class="keyword">const</span> *source_byte_ptr =</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>&#160;            <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">char</span> <span class="keyword">const </span>*<span class="keyword">&gt;</span>(source_ptr) + byte_offset +</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>&#160;            byte_offset_;</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>&#160;</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>&#160;        cutlass::arch::ldsm&lt;layout::RowMajor, Policy::LdsmShape::kCount&gt;(</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>&#160;            fetch_ptr[access_idx], source_byte_ptr);</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>&#160;      }</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>&#160;    }</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>&#160;  }</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>&#160;</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01259"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a0726a2e59e0eff3c40786d8712e47776"> 1259</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a0726a2e59e0eff3c40786d8712e47776">load_with_pointer_offset</a>(</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag,</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>&#160;    load_with_byte_offset(frag, pointer_offset * <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>&#160;  }</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>&#160;</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01269"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a3ff0b3e06a62a6d4d1d3aeb4bf491d87"> 1269</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a3ff0b3e06a62a6d4d1d3aeb4bf491d87">load</a>(</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag,</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>&#160;    load_with_byte_offset(frag, tile_offset, 0);</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>&#160;  }</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>&#160;</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01279"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a14bf57fe01b0419ef0a6b17730819c65"> 1279</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a14bf57fe01b0419ef0a6b17730819c65">load</a>(</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag,</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>&#160;    load_with_byte_offset(frag, tile_offset, pointer_offset * <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>&#160;  }</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>&#160;</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01291"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aac602e347a7e35680d0a0dd1b9e82951"> 1291</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aac602e347a7e35680d0a0dd1b9e82951">load_with_byte_offset</a>(</div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">Fragment</a> &amp;frag,</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">Index</a> pointer_offset = tile_offset.contiguous() *</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>&#160;                               InstructionShape::kContiguous /</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>&#160;                               Layout::kElementsPerAccess +</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>&#160;                           tile_offset.strided() * Shape::kStrided * stride_;</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>&#160;</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>&#160;    byte_offset += <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;AccessType&gt;::value</a> * pointer_offset / 8;</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>&#160;</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>&#160;    load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>&#160;  }</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>&#160;</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01316"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a909bd811645c74d84837ed21c3318b96"> 1316</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a909bd811645c74d84837ed21c3318b96">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>&#160;    k_group_idx_ = k_group % (Policy::kGroupsPerTile / kPartitionsK);</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>&#160;  }</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>&#160;};</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>&#160;</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>&#160;</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>&#160;    Operand Operand_,</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>&#160;    <span class="keywordtype">int</span> Crosswise,</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>&#160;    <span class="keywordtype">int</span> PartitionsK_&gt;</div><div class="line"><a name="l01346"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html"> 1346</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCrosswise.html">layout::ColumnMajorTensorOpMultiplicandCrosswise</a>&lt;</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>&#160;        sizeof_bits&lt;Element_&gt;::value, Crosswise&gt;,</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01353"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abc1e2caeaf199bb237021aedb568ff82"> 1353</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abc1e2caeaf199bb237021aedb568ff82">Shape</a> = Shape_;</div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>&#160;</div><div class="line"><a name="l01356"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad50d5b711b65113c24fb443f9a47d090"> 1356</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>&#160;</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">Operand::kB</a>,</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>&#160;                <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator for ColumnMajor Crosswise may &quot;</span></div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>&#160;                <span class="stringliteral">&quot;only be instantiated for B operand to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>&#160;</div><div class="line"><a name="l01363"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a63d8fb0bc5ff9156759fa24277aee9e0"> 1363</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>&#160;</div><div class="line"><a name="l01366"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ab727d22dc3746013f7a9e998b3311656"> 1366</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kCrosswise = Crosswise;</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>&#160;</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCrosswise.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCrosswise.html">cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise</a>&lt;</div><div class="line"><a name="l01370"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#add223eafdccc3e8557a1b797179ab645"> 1370</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, kCrosswise&gt;;</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160;</div><div class="line"><a name="l01373"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a4976d5d69018094eddecb44de711343e"> 1373</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a4976d5d69018094eddecb44de711343e">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160;</div><div class="line"><a name="l01377"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a4776e877963b81e7a1da91a7b5956034"> 1377</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160;</div><div class="line"><a name="l01380"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a63155c7e31f604d81cc80d8dd43aa4c1"> 1380</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>&#160;</div><div class="line"><a name="l01383"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad76e0d5c3390a5d148c76da1db5c75e2"> 1383</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160;</div><div class="line"><a name="l01386"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9"> 1386</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160;</div><div class="line"><a name="l01389"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2deff3a17ae49f6b0c6f7d46f3296144"> 1389</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2deff3a17ae49f6b0c6f7d46f3296144">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160;</div><div class="line"><a name="l01392"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0"> 1392</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160;</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160;      layout::PitchLinearShape&lt;Shape::kRow, Shape::kColumn&gt;, kOperand, Element,</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">layout::TensorOpMultiplicandCrosswise&lt;sizeof_bits&lt;Element_&gt;::value</a>,</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>&#160;                                            kCrosswise&gt;,</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape</a>&lt;InstructionShape::kRow,</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>&#160;                               InstructionShape::kColumn&gt;,</div><div class="line"><a name="l01401"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#af497c01bcf8f48ec2ec4a90df6eaec11"> 1401</a></span>&#160;      kOpDelta, kThreads, PartitionsK_&gt;;</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>&#160;</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>&#160;</div><div class="line"><a name="l01409"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68"> 1409</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>&#160;</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> iterator_;</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160;</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01418"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3ce87fe4f5ea64612fe20bc97dcab01d"> 1418</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3ce87fe4f5ea64612fe20bc97dcab01d">MmaTensorOpMultiplicandTileIterator</a>() {}</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160;</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01422"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a87790289d78b1b515f95f5e81626a236"> 1422</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a87790289d78b1b515f95f5e81626a236">MmaTensorOpMultiplicandTileIterator</a>(<a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, <span class="keywordtype">int</span> lane_id)</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;      : iterator_({ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>(), ref.<a class="code" href="classcutlass_1_1TensorRef.html#a191e88bc0fb310be655d700e937ab97c">stride</a>()}, lane_id) {}</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160;</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01427"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5c88fe11bac5ea0b60f3c73f4dc8b758"> 1427</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5c88fe11bac5ea0b60f3c73f4dc8b758">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2deff3a17ae49f6b0c6f7d46f3296144">LongIndex</a> offset) {</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160;    iterator_.add_pointer_offset(offset);</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>&#160;</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160;  }</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>&#160;</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01436"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aee6eda1ac83a4545e0220036871e8ab2"> 1436</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aee6eda1ac83a4545e0220036871e8ab2">add_tile_offset</a>(</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>&#160;    iterator_.add_tile_offset({tile_offset.row(), tile_offset.column()});</div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>&#160;</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>&#160;  }</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>&#160;</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01445"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aa0317bb349e4b16873cfe51dfa748519"> 1445</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aa0317bb349e4b16873cfe51dfa748519">operator++</a>() {</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>&#160;    ++iterator_;</div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>&#160;</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>&#160;  }</div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>&#160;</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01453"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ab319010cfbb0e20723c0fbdefac6a10e"> 1453</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ab319010cfbb0e20723c0fbdefac6a10e">operator--</a>() {</div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>&#160;    --iterator_;</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>&#160;</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>&#160;  }</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>&#160;</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01462"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2b8a09d931c351b3c252ee1a72147208"> 1462</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2b8a09d931c351b3c252ee1a72147208">operator+=</a>(</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>&#160;    add_tile_offset(PitchLinearCoord(tile_offset.row(), tile_offset.column()));</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>&#160;  }</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>&#160;</div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01471"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#adfcfe12e980652302eddabcf06911208"> 1471</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#adfcfe12e980652302eddabcf06911208">operator-=</a>(</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>&#160;    add_tile_offset(-PitchLinearCoord(tile_offset.row(), tile_offset.column()));</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>&#160;  }</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>&#160;</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01479"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5bf6f7434406ae011baad51c8f6134d7"> 1479</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5bf6f7434406ae011baad51c8f6134d7">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag)<span class="keyword"> const </span>{ iterator_.load(frag); }</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>&#160;</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01483"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6f96ec999bbddffcaca1a31aa31e9708"> 1483</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6f96ec999bbddffcaca1a31aa31e9708">load_with_pointer_offset</a>(</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag,</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160;    iterator_.load_with_pointer_offset(frag, pointer_offset);</div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160;  }</div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>&#160;</div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01493"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a0b3b6e84e68211479165f6bfce96421d"> 1493</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a0b3b6e84e68211479165f6bfce96421d">load_with_byte_offset</a>(</div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag,</div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>&#160;    iterator_.load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>&#160;  }</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>&#160;</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01503"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6d44b68261394c954c3667a061c0d91b"> 1503</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6d44b68261394c954c3667a061c0d91b">load</a>(</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag,</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>&#160;    assert(0);</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>&#160;  }</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>&#160;</div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01514"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abe224b64e7ed23246e233d7a407efdc8"> 1514</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abe224b64e7ed23246e233d7a407efdc8">load</a>(</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag,</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>&#160;    assert(0);</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>&#160;  }</div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>&#160;</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01527"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a82b17c0d55556b72697597851644bb53"> 1527</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a82b17c0d55556b72697597851644bb53">load_with_byte_offset</a>(</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">Fragment</a> &amp;frag,</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>&#160;    iterator_.load_with_byte_offset(</div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>&#160;        frag, {tile_offset.contiguous(), tile_offset.strided()}, byte_offset);</div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>&#160;  }</div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>&#160;</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01546"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3201247518a0b500753b719c92517768"> 1546</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3201247518a0b500753b719c92517768">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>&#160;    iterator_.set_kgroup_index(k_group); </div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>&#160;  }</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>&#160;};</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>&#160;</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>&#160;</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>&#160;    Operand Operand_,</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>&#160;    <span class="keywordtype">int</span> OpDelta_,</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>&#160;    <span class="keywordtype">int</span> Crosswise,</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>&#160;    <span class="keywordtype">int</span> PartitionsK_&gt;</div><div class="line"><a name="l01576"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html"> 1576</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>&#160;    Shape_, Operand_, Element_,</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>&#160;    <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCrosswise.html">layout::RowMajorTensorOpMultiplicandCrosswise</a>&lt;</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>&#160;        sizeof_bits&lt;Element_&gt;::value, Crosswise&gt;,</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>&#160;    InstructionShape_, OpDelta_, 32, PartitionsK_&gt; {</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01583"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad207cf1fa0534c8af6d571df376d8512"> 1583</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad207cf1fa0534c8af6d571df376d8512">Shape</a> = Shape_;</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>&#160;</div><div class="line"><a name="l01586"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#aea3b4653fc086476a28f8b9c7efc8c55"> 1586</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = Operand_;</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>&#160;</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>&#160;  <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(kOperand == <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">Operand::kA</a>,</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>&#160;                <span class="stringliteral">&quot;MmaTensorOpMultiplicandIterator for RowMajor Crosswise may &quot;</span></div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>&#160;                <span class="stringliteral">&quot;only be instantiated for A operand to warp-level Mma.&quot;</span>);</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>&#160;</div><div class="line"><a name="l01593"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a214ef88078b4c8d18031e0ea5380b72a"> 1593</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160;</div><div class="line"><a name="l01596"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a4272bab4dedfb6cb8a54ef5e6a087c56"> 1596</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kCrosswise = Crosswise;</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>&#160;</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCrosswise.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCrosswise.html">cutlass::layout::RowMajorTensorOpMultiplicandCrosswise</a>&lt;</div><div class="line"><a name="l01600"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a130187b87f2d284d9f3f9d1bcacd5a47"> 1600</a></span>&#160;      <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;Element_&gt;::value</a>, kCrosswise&gt;;</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160;</div><div class="line"><a name="l01603"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a9f08f1ae1bfbe2b3fdad0105d5f36cfc"> 1603</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a9f08f1ae1bfbe2b3fdad0105d5f36cfc">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160;</div><div class="line"><a name="l01607"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a3744dbf27ac3b792738eba665ae381e7"> 1607</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kOpDelta = OpDelta_;</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160;</div><div class="line"><a name="l01610"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a0b9caf53db250e8dc24316df2c710b53"> 1610</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;</div><div class="line"><a name="l01613"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ac2d29e0be22926585ddbfa22354c860d"> 1613</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160;</div><div class="line"><a name="l01616"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871"> 1616</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160;</div><div class="line"><a name="l01619"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9e19bef825c4f9eb203ad22149a79a5"> 1619</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9e19bef825c4f9eb203ad22149a79a5">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>&#160;</div><div class="line"><a name="l01622"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155"> 1622</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160;</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> = <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a>&lt;</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160;      layout::PitchLinearShape&lt;Shape::kColumn, Shape::kRow&gt;, kOperand, Element,</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">layout::TensorOpMultiplicandCrosswise&lt;sizeof_bits&lt;Element_&gt;::value</a>,</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160;                                            kCrosswise&gt;,</div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>&#160;      <a class="code" href="structcutlass_1_1layout_1_1PitchLinearShape.html">layout::PitchLinearShape</a>&lt;InstructionShape::kColumn,</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160;                               InstructionShape::kRow&gt;,</div><div class="line"><a name="l01631"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a8bcdfb8d9705c2b7fb0943d3ce8ab51e"> 1631</a></span>&#160;      kOpDelta, kThreads, PartitionsK_&gt;;</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160;</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>&#160;</div><div class="line"><a name="l01639"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5"> 1639</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160;</div><div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>&#160; <span class="keyword">private</span>:</div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">Base</a> iterator_;</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160;</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01648"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9ac79132faaf9d6913e13915f1d7cde"> 1648</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9ac79132faaf9d6913e13915f1d7cde">MmaTensorOpMultiplicandTileIterator</a>() {}</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>&#160;</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01652"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a42e843e212116c332aecd3468fa53a0e"> 1652</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a42e843e212116c332aecd3468fa53a0e">MmaTensorOpMultiplicandTileIterator</a>(<a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, <span class="keywordtype">int</span> lane_id)</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>&#160;      : iterator_({ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>(), ref.<a class="code" href="classcutlass_1_1TensorRef.html#a191e88bc0fb310be655d700e937ab97c">stride</a>()}, lane_id) {}</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>&#160;</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01657"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a283aff9bb995527e3a65752a3e2d8fe6"> 1657</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a283aff9bb995527e3a65752a3e2d8fe6">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9e19bef825c4f9eb203ad22149a79a5">LongIndex</a> offset) {</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>&#160;    iterator_.add_pointer_offset(offset);</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>&#160;</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>&#160;  }</div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>&#160;</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01666"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad8b8e35294c22e6b18be337ae3544c76"> 1666</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad8b8e35294c22e6b18be337ae3544c76">add_tile_offset</a>(</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>&#160;    iterator_.add_tile_offset({tile_offset.column(), tile_offset.row()});</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>&#160;</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>&#160;  }</div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>&#160;</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01675"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#aaad33f64f25dbcca8a34f577ad247595"> 1675</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#aaad33f64f25dbcca8a34f577ad247595">operator++</a>() {</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>&#160;    ++iterator_;</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>&#160;</div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>&#160;  }</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>&#160;</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01683"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ac698bc8cd44572e1f3ee52771fb2cefb"> 1683</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ac698bc8cd44572e1f3ee52771fb2cefb">operator--</a>() {</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>&#160;    --iterator_;</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>&#160;</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>&#160;  }</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>&#160;</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01692"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ab44ddbcd150470e1d234b2138ee1e8ef"> 1692</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ab44ddbcd150470e1d234b2138ee1e8ef">operator+=</a>(</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>&#160;    add_tile_offset(PitchLinearCoord(tile_offset.column(), tile_offset.row()));</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>&#160;  }</div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>&#160;</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01701"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a14abb245ffc13842b281db8f72b71361"> 1701</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">MmaTensorOpMultiplicandTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a14abb245ffc13842b281db8f72b71361">operator-=</a>(</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>&#160;    add_tile_offset(-PitchLinearCoord(tile_offset.column(), tile_offset.row()));</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>&#160;  }</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>&#160;</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01709"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a13030898f2eaab4b5d4136ff0932d649"> 1709</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a13030898f2eaab4b5d4136ff0932d649">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag)<span class="keyword"> const </span>{ iterator_.load(frag); }</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>&#160;</div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01713"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a2eb415e875f59697d8b38af6bfa540de"> 1713</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a2eb415e875f59697d8b38af6bfa540de">load_with_pointer_offset</a>(</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag,</div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>&#160;    iterator_.load_with_pointer_offset(frag, pointer_offset);</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>&#160;  }</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>&#160;</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01723"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a58c1c86c36a821bdbba0e7bbe59e79ec"> 1723</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a58c1c86c36a821bdbba0e7bbe59e79ec">load_with_byte_offset</a>(</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag,</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>&#160;    iterator_.load_with_byte_offset(frag, byte_offset);</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>&#160;  }</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>&#160;</div><div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01733"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#afde63a685ffcd99a9bbc1c9b6e121c9a"> 1733</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#afde63a685ffcd99a9bbc1c9b6e121c9a">load</a>(</div><div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag,</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>&#160;    assert(0);</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>&#160;  }</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>&#160;</div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01744"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a1c344341137b6d501556dbbf29dc53ac"> 1744</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a1c344341137b6d501556dbbf29dc53ac">load</a>(</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag,</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>&#160;    <span class="comment">// TODO</span></div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>&#160;    assert(0);</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>&#160;  }</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>&#160;</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01757"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a8514fa821eb580b6b80c33fc32c6b197"> 1757</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a8514fa821eb580b6b80c33fc32c6b197">load_with_byte_offset</a>(</div><div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">Fragment</a> &amp;frag,</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">Index</a> byte_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>&#160;    iterator_.load_with_byte_offset(</div><div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>&#160;        frag, {tile_offset.strided(), tile_offset.contiguous()}, byte_offset);</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>&#160;  }</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>&#160;</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01776"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a0f61bf6c060f3e0a471608f45b3580c3"> 1776</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a0f61bf6c060f3e0a471608f45b3580c3">set_kgroup_index</a>(<span class="keywordtype">int</span> k_group) {</div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>&#160;    iterator_.set_kgroup_index(k_group); </div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>&#160;  }</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>&#160;};</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>&#160;</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>&#160;    <span class="keyword">typename</span> Layout_,</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>&#160;    <span class="keyword">typename</span> OpDelta_&gt;</div><div class="line"><a name="l01794"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html"> 1794</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a>;</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>&#160;</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>&#160;</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l01810"></a><span class="lineno"> 1810</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>&#160;    <span class="keyword">typename</span> OpDelta_&gt;</div><div class="line"><a name="l01816"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html"> 1816</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a>&lt;</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>&#160;    Shape_, Element_, <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">layout::RowMajor</a>, InstructionShape_, OpDelta_&gt; {</div><div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>&#160;</div><div class="line"><a name="l01821"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a30f749a5f6451b8acfb90e1eef5e529c"> 1821</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a30f749a5f6451b8acfb90e1eef5e529c">Shape</a> = Shape_;</div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>&#160;</div><div class="line"><a name="l01824"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a431c4d5802a17ee889e35e42ece2e46f"> 1824</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6af73b7a14626c25aa554e2437ea3fc1df">Operand::kC</a>;</div><div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>&#160;</div><div class="line"><a name="l01827"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a14ee5c117cbf3985bea652c540fef1a5"> 1827</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>&#160;</div><div class="line"><a name="l01830"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a6c8cd9e5eb2068157e3a757637cb4ac1"> 1830</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">Layout</a> = <a class="code" href="classcutlass_1_1layout_1_1RowMajor.html">cutlass::layout::RowMajor</a>;</div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>&#160;</div><div class="line"><a name="l01833"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a0b99108d7d2ac1b2047c3d6ea51a6423"> 1833</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a0b99108d7d2ac1b2047c3d6ea51a6423">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>&#160;</div><div class="line"><a name="l01836"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad8269a57d4abf11261086c3f5cde979b"> 1836</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad8269a57d4abf11261086c3f5cde979b">OpDelta</a> = OpDelta_;</div><div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>&#160;</div><div class="line"><a name="l01839"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a4d099bfdea5ea89de5a9ed29c5707b39"> 1839</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>&#160;</div><div class="line"><a name="l01842"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a10caa46a91c46f5ad9a576fadab5ee46"> 1842</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>&#160;</div><div class="line"><a name="l01845"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8"> 1845</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>&#160;</div><div class="line"><a name="l01848"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a1bf4e5cf980f73ff62c0df8d6d2e99a9"> 1848</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a1bf4e5cf980f73ff62c0df8d6d2e99a9">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l01849"></a><span class="lineno"> 1849</span>&#160;</div><div class="line"><a name="l01851"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f"> 1851</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>&#160;</div><div class="line"><a name="l01854"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html"> 1854</a></span>&#160;  <span class="keyword">struct </span>Policy {</div><div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>&#160;        !(Shape::kRow % InstructionShape::kM) &amp;&amp;</div><div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>&#160;            !(Shape::kColumn % InstructionShape::kN),</div><div class="line"><a name="l01858"></a><span class="lineno"> 1858</span>&#160;        <span class="stringliteral">&quot;Shape of warp-level Mma must be divisible by operator shape.&quot;</span>);</div><div class="line"><a name="l01859"></a><span class="lineno"> 1859</span>&#160;</div><div class="line"><a name="l01860"></a><span class="lineno"> 1860</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(<a class="code" href="structcutlass_1_1platform_1_1is__same.html">platform::is_same&lt;TensorCoord, MatrixCoord&gt;::value</a>,</div><div class="line"><a name="l01861"></a><span class="lineno"> 1861</span>&#160;      <span class="stringliteral">&quot;Layouts must be defined for logical MatrixCoord coordinate space.&quot;</span>);</div><div class="line"><a name="l01862"></a><span class="lineno"> 1862</span>&#160;</div><div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1MatrixShape.html">MmaIterations</a> = <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape</a>&lt;Shape::kRow / InstructionShape::kM,</div><div class="line"><a name="l01865"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___093b5d2838ac5a742704ef62b5c8688f0.html#a29f781ce62fd4a067019ae90aa35c075"> 1865</a></span>&#160;                                      Shape::kColumn / InstructionShape::kN&gt;;</div><div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>&#160;  };</div><div class="line"><a name="l01867"></a><span class="lineno"> 1867</span>&#160;</div><div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>&#160;</div><div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>&#160;  <span class="comment">// Assume accumulator tile is an arrangement of 8-by-8 tiles replicated over the entire</span></div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>&#160;  <span class="comment">// shape, with each quad mapped to one row and each thread mapped to 1/4 of the elements</span></div><div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>&#160;  <span class="comment">// of that row. The accumulators within one row are assumed to be consecutive.</span></div><div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kElementsPerAccess = InstructionShape::kN / 4;</div><div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kRowsPerTile = 8;</div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kAccumulatorRows = InstructionShape::kM / kRowsPerTile;</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>&#160;</div><div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>&#160;</div><div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>&#160;</div><div class="line"><a name="l01884"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b"> 1884</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l01885"></a><span class="lineno"> 1885</span>&#160;</div><div class="line"><a name="l01886"></a><span class="lineno"> 1886</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>&#160;</div><div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>&#160;  <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> ref_;</div><div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>&#160;</div><div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>&#160;  </div><div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01895"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9b33490455b2ec60311e97712a5ae7da"> 1895</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9b33490455b2ec60311e97712a5ae7da">MmaTensorOpAccumulatorTileIterator</a>() { }</div><div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>&#160;</div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01899"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae84c72fbea0d63d08408fc6bceffe135"> 1899</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae84c72fbea0d63d08408fc6bceffe135">MmaTensorOpAccumulatorTileIterator</a>(</div><div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>&#160;  ):</div><div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>&#160;    ref_(ref) {</div><div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>&#160;</div><div class="line"><a name="l01905"></a><span class="lineno"> 1905</span>&#160;    <span class="keywordtype">int</span> quad = (lane_id &gt;&gt; 2);</div><div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>&#160;    <span class="keywordtype">int</span> lane_in_quad = (lane_id &amp; 3);</div><div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>&#160;</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>&#160;    <a class="code" href="structcutlass_1_1MatrixCoord.html">MatrixCoord</a> lane_offset(quad, lane_in_quad * kElementsPerAccess);</div><div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>&#160;</div><div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(lane_offset);</div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>&#160;  }</div><div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>&#160;</div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01915"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ade94421981f93d1623a260ec253b09da"> 1915</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ade94421981f93d1623a260ec253b09da">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a1bf4e5cf980f73ff62c0df8d6d2e99a9">LongIndex</a> offset) {</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(offset);</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>&#160;  }</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>&#160;</div><div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01922"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a3fff7e20df1a937e44aef89e468ef281"> 1922</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a3fff7e20df1a937e44aef89e468ef281">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>&#160;</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(tile_offset * <a class="code" href="namespacecutlass.html#a7419519fa453a121dfa5f26bf87318d9">make_Coord</a>(Shape::kRow, Shape::kColumn));</div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>&#160;</div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>&#160;  }</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>&#160;</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01931"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ada65ee7584604de9a688d88838399809"> 1931</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ada65ee7584604de9a688d88838399809">operator++</a>() {</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>&#160;  }</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>&#160;</div><div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01938"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#abba62827ecc9247b59e1d03898c5feb2"> 1938</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#abba62827ecc9247b59e1d03898c5feb2">operator--</a>() {</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>&#160;  }</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>&#160;</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01945"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad48f385d6822485184461d82bd70d4de"> 1945</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad48f385d6822485184461d82bd70d4de">operator+=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>&#160;    add_tile_offset(tile_offset);</div><div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>&#160;  }</div><div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>&#160;</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01952"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#affd5c6e12f2fc9c00ec08d43e8f8d2f6"> 1952</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#affd5c6e12f2fc9c00ec08d43e8f8d2f6">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>&#160;    add_tile_offset(-tile_offset);</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>&#160;  }</div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>&#160;</div><div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l01959"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a233b7f950eb27053b5c596dbd0ee7eb6"> 1959</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a233b7f950eb27053b5c596dbd0ee7eb6">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>&#160;    load_with_pointer_offset(frag, 0);</div><div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>&#160;  }</div><div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>&#160;</div><div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01965"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5804aaa9ff4b99b8e1baa0355d34e0c1"> 1965</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5804aaa9ff4b99b8e1baa0355d34e0c1">load_with_pointer_offset</a>(</div><div class="line"><a name="l01966"></a><span class="lineno"> 1966</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l01967"></a><span class="lineno"> 1967</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l01968"></a><span class="lineno"> 1968</span>&#160;  </div><div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>&#160;</div><div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_n = 0; mma_n &lt; Policy::MmaIterations::kColumn; ++mma_n) {</div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_m = 0; mma_m &lt; Policy::MmaIterations::kRow; ++mma_m) {</div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>&#160;        </div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>&#160;        <span class="keywordtype">int</span> mma_accum_start = kAccumulatorRows * kElementsPerAccess * </div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>&#160;          (mma_n * Policy::MmaIterations::kRow + mma_m);</div><div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>&#160;</div><div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> row = 0; row &lt; kAccumulatorRows; ++row) {</div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>&#160;          <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> col = 0; col &lt; kElementsPerAccess; ++col) {</div><div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>&#160;            <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM * OpDelta::kRow +</div><div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>&#160;                          row * kRowsPerTile;</div><div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>&#160;            <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN * OpDelta::kColumn + col;</div><div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>&#160;</div><div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>&#160;            frag[mma_accum_start + row * kElementsPerAccess + col] = offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a8758907a1c9b1fcd00e7ece626d03b76">at</a>({accum_m, accum_n});</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>&#160;          }</div><div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>&#160;        }</div><div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>&#160;      }</div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>&#160;    }</div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>&#160;  }</div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>&#160;</div><div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l01997"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a7f9e9b46f9dc826b7f677bcd17bcfe66"> 1997</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a7f9e9b46f9dc826b7f677bcd17bcfe66">load_with_byte_offset</a>(</div><div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>&#160;</div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>&#160;    load_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>&#160;  }</div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>&#160;</div><div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02006"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a56f39dc886dc0888713d623687d9ed90"> 2006</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a56f39dc886dc0888713d623687d9ed90">load</a>(</div><div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>&#160;</div><div class="line"><a name="l02010"></a><span class="lineno"> 2010</span>&#160;    load(frag, tile_offset, 0);</div><div class="line"><a name="l02011"></a><span class="lineno"> 2011</span>&#160;  }</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</span>&#160;</div><div class="line"><a name="l02014"></a><span class="lineno"> 2014</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02015"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a63bfeacfdc5a1a13b1ae9a01e65ba3ee"> 2015</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a63bfeacfdc5a1a13b1ae9a01e65ba3ee">load</a>(</div><div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,             </div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>&#160;</div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>&#160;    load_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>&#160;  }</div><div class="line"><a name="l02022"></a><span class="lineno"> 2022</span>&#160;</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02025"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae9b9762870c51eadb90c795c65d638b0"> 2025</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae9b9762870c51eadb90c795c65d638b0">store</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> <span class="keyword">const</span> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>&#160;    store_with_pointer_offset(frag, 0);</div><div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>&#160;  }</div><div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>&#160;</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02031"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad70395a1fbd33b034888f797e1bb8e30"> 2031</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad70395a1fbd33b034888f797e1bb8e30">store_with_pointer_offset</a>(</div><div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</span>&#160;  </div><div class="line"><a name="l02035"></a><span class="lineno"> 2035</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>&#160;</div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_n = 0; mma_n &lt; Policy::MmaIterations::kColumn; ++mma_n) {</div><div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_m = 0; mma_m &lt; Policy::MmaIterations::kRow; ++mma_m) {</div><div class="line"><a name="l02042"></a><span class="lineno"> 2042</span>&#160;        </div><div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>&#160;        <span class="keywordtype">int</span> mma_accum_start = kAccumulatorRows * kElementsPerAccess * </div><div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>&#160;          (mma_n * Policy::MmaIterations::kRow + mma_m);</div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>&#160;</div><div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> row = 0; row &lt; kAccumulatorRows; ++row) {</div><div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>&#160;          <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> col = 0; col &lt; kElementsPerAccess; ++col) {</div><div class="line"><a name="l02050"></a><span class="lineno"> 2050</span>&#160;            <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM * OpDelta::kRow +</div><div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>&#160;                          row * kRowsPerTile;</div><div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>&#160;            <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN * OpDelta::kColumn + col;</div><div class="line"><a name="l02053"></a><span class="lineno"> 2053</span>&#160;            <span class="keywordtype">int</span> idx = mma_accum_start + row * kElementsPerAccess + col;</div><div class="line"><a name="l02054"></a><span class="lineno"> 2054</span>&#160;</div><div class="line"><a name="l02055"></a><span class="lineno"> 2055</span>&#160;            offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a8758907a1c9b1fcd00e7ece626d03b76">at</a>({accum_m, accum_n}) = frag[idx];</div><div class="line"><a name="l02056"></a><span class="lineno"> 2056</span>&#160;          }</div><div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>&#160;        }</div><div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>&#160;      }</div><div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>&#160;    }</div><div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>&#160;  }</div><div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>&#160;</div><div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02064"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5d008e10ed2dc1572a2d9392a41d4dac"> 2064</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5d008e10ed2dc1572a2d9392a41d4dac">store_with_byte_offset</a>(</div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>&#160;</div><div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>&#160;    store_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>&#160;  }</div><div class="line"><a name="l02070"></a><span class="lineno"> 2070</span>&#160;</div><div class="line"><a name="l02072"></a><span class="lineno"> 2072</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02073"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#af6507b45143ec47c96e03c578af82e33"> 2073</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#af6507b45143ec47c96e03c578af82e33">store</a>(</div><div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02076"></a><span class="lineno"> 2076</span>&#160;</div><div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>&#160;    store(frag, tile_offset, 0);</div><div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>&#160;  }</div><div class="line"><a name="l02079"></a><span class="lineno"> 2079</span>&#160;</div><div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02082"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a86ef850cea2f61213ca9aa53a2c78ff1"> 2082</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a86ef850cea2f61213ca9aa53a2c78ff1">store</a>(</div><div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">Fragment</a> <span class="keyword">const</span> &amp;frag,</div><div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l02089"></a><span class="lineno"> 2089</span>&#160;    store_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02090"></a><span class="lineno"> 2090</span>&#160;  }</div><div class="line"><a name="l02091"></a><span class="lineno"> 2091</span>&#160;};</div><div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>&#160;</div><div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>&#160;</div><div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l02109"></a><span class="lineno"> 2109</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>&#160;    <span class="keyword">typename</span> OpDelta_&gt;</div><div class="line"><a name="l02113"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html"> 2113</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a>&lt;Shape_, Element_,</div><div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>&#160;                                         <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">layout::ColumnMajor</a>,</div><div class="line"><a name="l02115"></a><span class="lineno"> 2115</span>&#160;                                         InstructionShape_, OpDelta_&gt; {</div><div class="line"><a name="l02116"></a><span class="lineno"> 2116</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>&#160;</div><div class="line"><a name="l02119"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a546ea293ab08e4474731b3e6e61bc019"> 2119</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a546ea293ab08e4474731b3e6e61bc019">Shape</a> = Shape_;</div><div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>&#160;</div><div class="line"><a name="l02122"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ab1d2010f80a463b38f41e0f7317b4976"> 2122</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6af73b7a14626c25aa554e2437ea3fc1df">Operand::kC</a>;</div><div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>&#160;</div><div class="line"><a name="l02125"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa505ebe00fac7b08e598bd6be3e4a9ec"> 2125</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>&#160;</div><div class="line"><a name="l02128"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a61620a099fbc4ab7f1e2f02db47c5680"> 2128</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">Layout</a> = <a class="code" href="classcutlass_1_1layout_1_1ColumnMajor.html">cutlass::layout::ColumnMajor</a>;</div><div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>&#160;</div><div class="line"><a name="l02131"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aabb62dc50c032e4691e6d96ea6740f12"> 2131</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aabb62dc50c032e4691e6d96ea6740f12">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>&#160;</div><div class="line"><a name="l02134"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac937a12e2f235d6465ecbf2142cc76cd"> 2134</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac937a12e2f235d6465ecbf2142cc76cd">OpDelta</a> = OpDelta_;</div><div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>&#160;</div><div class="line"><a name="l02137"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a7ef8f84a0bfed1a42a0a0f3b01814ecf"> 2137</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>&#160;</div><div class="line"><a name="l02140"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a9940cb98cf8d7e5bd21c3cf6886557ef"> 2140</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>&#160;</div><div class="line"><a name="l02143"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741"> 2143</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>&#160;</div><div class="line"><a name="l02146"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af415b1bda869f2ef506c6a92dafc5829"> 2146</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af415b1bda869f2ef506c6a92dafc5829">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>&#160;</div><div class="line"><a name="l02149"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63"> 2149</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>&#160;</div><div class="line"><a name="l02152"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___0d35fa5dc4e4b4f72784c943fd857fc1d.html"> 2152</a></span>&#160;  <span class="keyword">struct </span>Policy {</div><div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l02154"></a><span class="lineno"> 2154</span>&#160;        !(Shape::kRow % InstructionShape::kM) &amp;&amp;</div><div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>&#160;            !(Shape::kColumn % InstructionShape::kN),</div><div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>&#160;        <span class="stringliteral">&quot;Shape of warp-level Mma must be divisible by operator shape.&quot;</span>);</div><div class="line"><a name="l02157"></a><span class="lineno"> 2157</span>&#160;</div><div class="line"><a name="l02158"></a><span class="lineno"> 2158</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(<a class="code" href="structcutlass_1_1platform_1_1is__same.html">platform::is_same&lt;TensorCoord, MatrixCoord&gt;::value</a>,</div><div class="line"><a name="l02159"></a><span class="lineno"> 2159</span>&#160;      <span class="stringliteral">&quot;Layouts must be defined for logical MatrixCoord coordinate space.&quot;</span>);</div><div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>&#160;</div><div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1MatrixShape.html">MmaIterations</a> = <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape</a>&lt;Shape::kRow / InstructionShape::kM,</div><div class="line"><a name="l02163"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___0d35fa5dc4e4b4f72784c943fd857fc1d.html#a45aaaf52d132111ece0b1a5463da5a0e"> 2163</a></span>&#160;                                      Shape::kColumn / InstructionShape::kN&gt;;</div><div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>&#160;  };</div><div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>&#160;</div><div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>&#160;</div><div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>&#160;  <span class="comment">// Assume accumulator tile is an arrangement of 8-by-8 tiles replicated over the entire</span></div><div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>&#160;  <span class="comment">// shape, with each quad mapped to one row and each thread mapped to 1/4 of the elements</span></div><div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>&#160;  <span class="comment">// of that row. The accumulators within one row are assumed to be consecutive.</span></div><div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kElementsPerAccess = InstructionShape::kN / 4;</div><div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kRowsPerTile = 8;</div><div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>&#160; <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kAccumulatorRows = InstructionShape::kM / kRowsPerTile;</div><div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>&#160;</div><div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l02176"></a><span class="lineno"> 2176</span>&#160;</div><div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>&#160;</div><div class="line"><a name="l02182"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1"> 2182</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l02183"></a><span class="lineno"> 2183</span>&#160;</div><div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>&#160;</div><div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>&#160;  <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> ref_;</div><div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>&#160;</div><div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>&#160;  </div><div class="line"><a name="l02192"></a><span class="lineno"> 2192</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02193"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5b36b747c47da28a51a5ec94fa51edef"> 2193</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5b36b747c47da28a51a5ec94fa51edef">MmaTensorOpAccumulatorTileIterator</a>() { }</div><div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>&#160;</div><div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02197"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa177f1e6b921b9d1b423ebc05a1f2e0e"> 2197</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa177f1e6b921b9d1b423ebc05a1f2e0e">MmaTensorOpAccumulatorTileIterator</a>(</div><div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>&#160;  ):</div><div class="line"><a name="l02201"></a><span class="lineno"> 2201</span>&#160;    ref_(ref) {</div><div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>&#160;</div><div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>&#160;    <span class="keywordtype">int</span> quad = (lane_id &gt;&gt; 2);</div><div class="line"><a name="l02204"></a><span class="lineno"> 2204</span>&#160;    <span class="keywordtype">int</span> lane_in_quad = (lane_id &amp; 3);</div><div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>&#160;</div><div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>&#160;    <a class="code" href="structcutlass_1_1MatrixCoord.html">MatrixCoord</a> lane_offset(quad, lane_in_quad * kElementsPerAccess);</div><div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>&#160;</div><div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(lane_offset);</div><div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>&#160;  }</div><div class="line"><a name="l02210"></a><span class="lineno"> 2210</span>&#160;</div><div class="line"><a name="l02212"></a><span class="lineno"> 2212</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02213"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a1bd195c67970a5139c1c4f23e6c5f870"> 2213</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a1bd195c67970a5139c1c4f23e6c5f870">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af415b1bda869f2ef506c6a92dafc5829">LongIndex</a> offset) {</div><div class="line"><a name="l02214"></a><span class="lineno"> 2214</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(offset);</div><div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>&#160;  }</div><div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>&#160;</div><div class="line"><a name="l02219"></a><span class="lineno"> 2219</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02220"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a9f16e361268ea077a08a0182984db261"> 2220</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a9f16e361268ea077a08a0182984db261">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02221"></a><span class="lineno"> 2221</span>&#160;</div><div class="line"><a name="l02222"></a><span class="lineno"> 2222</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(tile_offset * <a class="code" href="namespacecutlass.html#a7419519fa453a121dfa5f26bf87318d9">make_Coord</a>(Shape::kRow, Shape::kColumn));</div><div class="line"><a name="l02223"></a><span class="lineno"> 2223</span>&#160;</div><div class="line"><a name="l02224"></a><span class="lineno"> 2224</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>&#160;  }</div><div class="line"><a name="l02226"></a><span class="lineno"> 2226</span>&#160;</div><div class="line"><a name="l02228"></a><span class="lineno"> 2228</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02229"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a085b222207880b579b8ffa91c905e071"> 2229</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a085b222207880b579b8ffa91c905e071">operator++</a>() {</div><div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l02231"></a><span class="lineno"> 2231</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02232"></a><span class="lineno"> 2232</span>&#160;  }</div><div class="line"><a name="l02233"></a><span class="lineno"> 2233</span>&#160;</div><div class="line"><a name="l02235"></a><span class="lineno"> 2235</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02236"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac6dc64ff8af8291455978f9fd168c6fc"> 2236</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac6dc64ff8af8291455978f9fd168c6fc">operator--</a>() {</div><div class="line"><a name="l02237"></a><span class="lineno"> 2237</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02239"></a><span class="lineno"> 2239</span>&#160;  }</div><div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>&#160;</div><div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02243"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af8d0bb15e6c967e41c175d7989c728b2"> 2243</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af8d0bb15e6c967e41c175d7989c728b2">operator+=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02244"></a><span class="lineno"> 2244</span>&#160;    add_tile_offset(tile_offset);</div><div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>&#160;  }</div><div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>&#160;</div><div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02250"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a0e3aca80cfc279e9e207a3044e925dc9"> 2250</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a0e3aca80cfc279e9e207a3044e925dc9">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>&#160;    add_tile_offset(-tile_offset);</div><div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>&#160;  }</div><div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>&#160;</div><div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02257"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaeee8d14c95678428d8d2ba36e76b9d0"> 2257</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaeee8d14c95678428d8d2ba36e76b9d0">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>&#160;    load_with_pointer_offset(frag, 0);</div><div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>&#160;  }</div><div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>&#160;</div><div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02263"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a570f020d67995c1a7232e14ec07e3b0c"> 2263</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a570f020d67995c1a7232e14ec07e3b0c">load_with_pointer_offset</a>(</div><div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>&#160;  </div><div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>&#160;</div><div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>&#160; 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       <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> row = 0; row &lt; kAccumulatorRows; ++row) {</div><div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>&#160;          <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> col = 0; col &lt; kElementsPerAccess; ++col) {</div><div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>&#160;            <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM * OpDelta::kRow +</div><div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>&#160;                          row * kRowsPerTile;</div><div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>&#160;            <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN * OpDelta::kColumn + col;</div><div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>&#160;            <span class="keywordtype">int</span> idx = mma_accum_start + row * kElementsPerAccess + col;</div><div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>&#160;</div><div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>&#160;            frag[idx] = offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a8758907a1c9b1fcd00e7ece626d03b76">at</a>({accum_m, accum_n});</div><div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>&#160;          }</div><div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>&#160;        }</div><div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>&#160;      }</div><div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>&#160;    }</div><div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>&#160;  }</div><div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>&#160;</div><div class="line"><a name="l02295"></a><span class="lineno"> 2295</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02296"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5a76314f07d7a5ddeed7a566228acc4d"> 2296</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5a76314f07d7a5ddeed7a566228acc4d">load_with_byte_offset</a>(</div><div class="line"><a name="l02297"></a><span class="lineno"> 2297</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02298"></a><span class="lineno"> 2298</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>&#160;</div><div class="line"><a name="l02300"></a><span class="lineno"> 2300</span>&#160;    load_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>&#160;  }</div><div class="line"><a name="l02302"></a><span class="lineno"> 2302</span>&#160;</div><div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02305"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a4a5c6c8dec5efca214619756b3e38bfc"> 2305</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a4a5c6c8dec5efca214619756b3e38bfc">load</a>(</div><div class="line"><a name="l02306"></a><span class="lineno"> 2306</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02307"></a><span class="lineno"> 2307</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02308"></a><span class="lineno"> 2308</span>&#160;</div><div class="line"><a name="l02309"></a><span class="lineno"> 2309</span>&#160;    load(frag, tile_offset, 0);</div><div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>&#160;  }</div><div class="line"><a name="l02311"></a><span class="lineno"> 2311</span>&#160;</div><div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02314"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae44384c7f4d58288c04ac4fabfd86c25"> 2314</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae44384c7f4d58288c04ac4fabfd86c25">load</a>(</div><div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,             </div><div class="line"><a name="l02317"></a><span class="lineno"> 2317</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>&#160;</div><div class="line"><a name="l02319"></a><span class="lineno"> 2319</span>&#160;    load_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02320"></a><span class="lineno"> 2320</span>&#160;  }</div><div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>&#160;</div><div class="line"><a name="l02323"></a><span class="lineno"> 2323</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02324"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a313942884867ffbe05c046a2ae577f7f"> 2324</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a313942884867ffbe05c046a2ae577f7f">store</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> <span class="keyword">const</span> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>&#160;    store_with_pointer_offset(frag, 0);</div><div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>&#160;  }</div><div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>&#160;</div><div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02330"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaea5e34d1fd1a462103790268c6d549c"> 2330</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaea5e34d1fd1a462103790268c6d549c">store_with_pointer_offset</a>(</div><div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>&#160;  </div><div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>&#160;</div><div class="line"><a name="l02337"></a><span class="lineno"> 2337</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02338"></a><span class="lineno"> 2338</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_n = 0; mma_n &lt; Policy::MmaIterations::kColumn; ++mma_n) {</div><div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_m = 0; mma_m &lt; Policy::MmaIterations::kRow; ++mma_m) {</div><div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>&#160;        </div><div class="line"><a name="l02342"></a><span class="lineno"> 2342</span>&#160;        <span class="keywordtype">int</span> mma_accum_start = kAccumulatorRows * kElementsPerAccess * </div><div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>&#160;          (mma_n * Policy::MmaIterations::kRow + mma_m);</div><div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>&#160;</div><div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>&#160;        <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02346"></a><span class="lineno"> 2346</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> row = 0; row &lt; kAccumulatorRows; ++row) {</div><div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>&#160;          <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02348"></a><span class="lineno"> 2348</span>&#160;          <span class="keywordflow">for</span> (<span class="keywordtype">int</span> col = 0; col &lt; kElementsPerAccess; ++col) {</div><div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>&#160;            <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM * OpDelta::kRow +</div><div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>&#160;                          row * kRowsPerTile;</div><div class="line"><a name="l02351"></a><span class="lineno"> 2351</span>&#160;            <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN * OpDelta::kColumn + col;</div><div class="line"><a name="l02352"></a><span class="lineno"> 2352</span>&#160;            <span class="keywordtype">int</span> idx = mma_accum_start + row * kElementsPerAccess + col;</div><div class="line"><a name="l02353"></a><span class="lineno"> 2353</span>&#160;            </div><div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>&#160;            offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a8758907a1c9b1fcd00e7ece626d03b76">at</a>({accum_m, accum_n}) = frag[idx];</div><div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>&#160;          }</div><div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>&#160;        }</div><div class="line"><a name="l02357"></a><span class="lineno"> 2357</span>&#160;      }</div><div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>&#160;    }</div><div class="line"><a name="l02359"></a><span class="lineno"> 2359</span>&#160;  }</div><div class="line"><a name="l02360"></a><span class="lineno"> 2360</span>&#160;</div><div class="line"><a name="l02362"></a><span class="lineno"> 2362</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02363"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae68482e62a32c98bb5c2aaf64a835586"> 2363</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae68482e62a32c98bb5c2aaf64a835586">store_with_byte_offset</a>(</div><div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02365"></a><span class="lineno"> 2365</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>&#160;</div><div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>&#160;    store_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02368"></a><span class="lineno"> 2368</span>&#160;  }</div><div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>&#160;</div><div class="line"><a name="l02371"></a><span class="lineno"> 2371</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02372"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a72d7ffbb1e1558425e1e7370e2e3ec48"> 2372</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a72d7ffbb1e1558425e1e7370e2e3ec48">store</a>(</div><div class="line"><a name="l02373"></a><span class="lineno"> 2373</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02374"></a><span class="lineno"> 2374</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>&#160;</div><div class="line"><a name="l02376"></a><span class="lineno"> 2376</span>&#160;    store(frag, tile_offset, 0);</div><div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>&#160;  }</div><div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>&#160;</div><div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02381"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa1789d85a3ac04dd71be4bddff2dab5a"> 2381</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa1789d85a3ac04dd71be4bddff2dab5a">store</a>(</div><div class="line"><a name="l02383"></a><span class="lineno"> 2383</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">Fragment</a> <span class="keyword">const</span> &amp;frag,</div><div class="line"><a name="l02385"></a><span class="lineno"> 2385</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l02387"></a><span class="lineno"> 2387</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l02388"></a><span class="lineno"> 2388</span>&#160;    store_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>&#160;  }</div><div class="line"><a name="l02390"></a><span class="lineno"> 2390</span>&#160;};</div><div class="line"><a name="l02391"></a><span class="lineno"> 2391</span>&#160;</div><div class="line"><a name="l02393"></a><span class="lineno"> 2393</span>&#160;</div><div class="line"><a name="l02402"></a><span class="lineno"> 2402</span>&#160;</div><div class="line"><a name="l02403"></a><span class="lineno"> 2403</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l02405"></a><span class="lineno"> 2405</span>&#160;    <span class="keyword">typename</span> Shape_,</div><div class="line"><a name="l02407"></a><span class="lineno"> 2407</span>&#160;    <span class="keyword">typename</span> Element_,</div><div class="line"><a name="l02409"></a><span class="lineno"> 2409</span>&#160;    <span class="keyword">typename</span> InstructionShape_,</div><div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>&#160;    <span class="keyword">typename</span> OpDelta_,</div><div class="line"><a name="l02414"></a><span class="lineno"> 2414</span>&#160;    <span class="keywordtype">int</span> InterleavedN&gt;</div><div class="line"><a name="l02415"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html"> 2415</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a>&lt;</div><div class="line"><a name="l02416"></a><span class="lineno"> 2416</span>&#160;    Shape_, Element_, <a class="code" href="namespacecutlass.html">cutlass</a>::<a class="code" href="structcutlass_1_1layout_1_1ColumnMajorInterleaved.html">layout::ColumnMajorInterleaved</a>&lt;InterleavedN&gt;,</div><div class="line"><a name="l02417"></a><span class="lineno"> 2417</span>&#160;    InstructionShape_, OpDelta_&gt; {</div><div class="line"><a name="l02418"></a><span class="lineno"> 2418</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l02419"></a><span class="lineno"> 2419</span>&#160;</div><div class="line"><a name="l02421"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa80ed8a40b27d0d0e5b5f8577fc24436"> 2421</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa80ed8a40b27d0d0e5b5f8577fc24436">Shape</a> = Shape_;</div><div class="line"><a name="l02422"></a><span class="lineno"> 2422</span>&#160;</div><div class="line"><a name="l02424"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#abe358f8cbcc78d00b121d80ffadff905"> 2424</a></span>&#160;  <span class="keyword">static</span> Operand <span class="keyword">const</span> kOperand = <a class="code" href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6af73b7a14626c25aa554e2437ea3fc1df">Operand::kC</a>;</div><div class="line"><a name="l02425"></a><span class="lineno"> 2425</span>&#160;</div><div class="line"><a name="l02427"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa0a0eaaf6d9cb09c927d60d607cf872d"> 2427</a></span>&#160;  <span class="keyword">using</span> Element = Element_;</div><div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>&#160;</div><div class="line"><a name="l02430"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ab376a9049849d37e9f68cf8ffe19d338"> 2430</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorInterleaved.html">Layout</a> = <a class="code" href="structcutlass_1_1layout_1_1ColumnMajorInterleaved.html">cutlass::layout::ColumnMajorInterleaved&lt;InterleavedN&gt;</a>;</div><div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>&#160;</div><div class="line"><a name="l02433"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a784a554c0b5d90d36e8df22df8e4d80c"> 2433</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a784a554c0b5d90d36e8df22df8e4d80c">InstructionShape</a> = InstructionShape_;</div><div class="line"><a name="l02434"></a><span class="lineno"> 2434</span>&#160;</div><div class="line"><a name="l02436"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a1e951937f4ef558a694519404d757bdb"> 2436</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a1e951937f4ef558a694519404d757bdb">OpDelta</a> = OpDelta_;</div><div class="line"><a name="l02437"></a><span class="lineno"> 2437</span>&#160;</div><div class="line"><a name="l02439"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ace40436c7aaeee19e49ac1ab917300a6"> 2439</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = 32;</div><div class="line"><a name="l02440"></a><span class="lineno"> 2440</span>&#160;</div><div class="line"><a name="l02442"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aacd6aa4a888b7157a5d4276b9900becf"> 2442</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> = <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef&lt;Element, Layout&gt;</a>;</div><div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>&#160;</div><div class="line"><a name="l02445"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4"> 2445</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">TensorRef::Index</a>;</div><div class="line"><a name="l02446"></a><span class="lineno"> 2446</span>&#160;</div><div class="line"><a name="l02448"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#affeae7791be815ff2e0c99c60b079dab"> 2448</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#affeae7791be815ff2e0c99c60b079dab">LongIndex</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">TensorRef::LongIndex</a>;</div><div class="line"><a name="l02449"></a><span class="lineno"> 2449</span>&#160;</div><div class="line"><a name="l02451"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55"> 2451</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> = <span class="keyword">typename</span> <a class="code" href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">TensorRef::TensorCoord</a>;</div><div class="line"><a name="l02452"></a><span class="lineno"> 2452</span>&#160;</div><div class="line"><a name="l02454"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___03822d9be37f3725022005a5434441f22.html"> 2454</a></span>&#160;  <span class="keyword">struct </span>Policy {</div><div class="line"><a name="l02455"></a><span class="lineno"> 2455</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l02456"></a><span class="lineno"> 2456</span>&#160;        !(Shape::kRow % InstructionShape::kM) &amp;&amp;</div><div class="line"><a name="l02457"></a><span class="lineno"> 2457</span>&#160;            !(Shape::kColumn % InstructionShape::kN),</div><div class="line"><a name="l02458"></a><span class="lineno"> 2458</span>&#160;        <span class="stringliteral">&quot;Shape of warp-level Mma must be divisible by operator shape.&quot;</span>);</div><div class="line"><a name="l02459"></a><span class="lineno"> 2459</span>&#160;</div><div class="line"><a name="l02460"></a><span class="lineno"> 2460</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(<a class="code" href="structcutlass_1_1platform_1_1is__same.html">platform::is_same&lt;TensorCoord, MatrixCoord&gt;::value</a>,</div><div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>&#160;      <span class="stringliteral">&quot;Layouts must be defined for logical MatrixCoord coordinate space.&quot;</span>);</div><div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>&#160;</div><div class="line"><a name="l02464"></a><span class="lineno"> 2464</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1MatrixShape.html">MmaIterations</a> = <a class="code" href="structcutlass_1_1MatrixShape.html">MatrixShape</a>&lt;Shape::kRow / InstructionShape::kM,</div><div class="line"><a name="l02465"></a><span class="lineno"><a class="line" href="structcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___03822d9be37f3725022005a5434441f22.html#a9aa3c185c4cf51ba6b29f2bdfae2ce6c"> 2465</a></span>&#160;                                      Shape::kColumn / InstructionShape::kN&gt;;</div><div class="line"><a name="l02466"></a><span class="lineno"> 2466</span>&#160;  };</div><div class="line"><a name="l02467"></a><span class="lineno"> 2467</span>&#160;</div><div class="line"><a name="l02468"></a><span class="lineno"> 2468</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l02469"></a><span class="lineno"> 2469</span>&#160;</div><div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kElementsPerAccess = 2;</div><div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>&#160;</div><div class="line"><a name="l02472"></a><span class="lineno"> 2472</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l02473"></a><span class="lineno"> 2473</span>&#160;</div><div class="line"><a name="l02474"></a><span class="lineno"> 2474</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>&#160;  <span class="comment">// Derived quantities</span></div><div class="line"><a name="l02476"></a><span class="lineno"> 2476</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l02477"></a><span class="lineno"> 2477</span>&#160;</div><div class="line"><a name="l02478"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae"> 2478</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> = Array&lt;Element, kElementsPerAccess&gt;;</div><div class="line"><a name="l02479"></a><span class="lineno"> 2479</span>&#160;</div><div class="line"><a name="l02481"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94"> 2481</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> = Array&lt;Element, Shape::kCount / kThreads&gt;;</div><div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>&#160;</div><div class="line"><a name="l02483"></a><span class="lineno"> 2483</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l02484"></a><span class="lineno"> 2484</span>&#160;</div><div class="line"><a name="l02486"></a><span class="lineno"> 2486</span>&#160;  <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> ref_;</div><div class="line"><a name="l02487"></a><span class="lineno"> 2487</span>&#160;</div><div class="line"><a name="l02488"></a><span class="lineno"> 2488</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l02489"></a><span class="lineno"> 2489</span>&#160;  </div><div class="line"><a name="l02491"></a><span class="lineno"> 2491</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02492"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaad8afd436ee02d232e37aebdd0e2a8e"> 2492</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaad8afd436ee02d232e37aebdd0e2a8e">MmaTensorOpAccumulatorTileIterator</a>() { }</div><div class="line"><a name="l02493"></a><span class="lineno"> 2493</span>&#160;</div><div class="line"><a name="l02495"></a><span class="lineno"> 2495</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02496"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ada9807d73db23e2388054d3a89e6cd35"> 2496</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ada9807d73db23e2388054d3a89e6cd35">MmaTensorOpAccumulatorTileIterator</a>(</div><div class="line"><a name="l02497"></a><span class="lineno"> 2497</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> <span class="keyword">const</span> &amp;ref, </div><div class="line"><a name="l02498"></a><span class="lineno"> 2498</span>&#160;    <span class="keywordtype">int</span> lane_id</div><div class="line"><a name="l02499"></a><span class="lineno"> 2499</span>&#160;  ):</div><div class="line"><a name="l02500"></a><span class="lineno"> 2500</span>&#160;    ref_(ref) {</div><div class="line"><a name="l02501"></a><span class="lineno"> 2501</span>&#160;</div><div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>&#160;    <span class="keywordtype">int</span> quad = (lane_id &gt;&gt; 2);</div><div class="line"><a name="l02503"></a><span class="lineno"> 2503</span>&#160;    <span class="keywordtype">int</span> lane_in_quad = (lane_id &amp; 3);</div><div class="line"><a name="l02504"></a><span class="lineno"> 2504</span>&#160;</div><div class="line"><a name="l02505"></a><span class="lineno"> 2505</span>&#160;    <a class="code" href="structcutlass_1_1MatrixCoord.html">MatrixCoord</a> lane_offset(quad, lane_in_quad * kElementsPerAccess);</div><div class="line"><a name="l02506"></a><span class="lineno"> 2506</span>&#160;</div><div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(lane_offset);</div><div class="line"><a name="l02508"></a><span class="lineno"> 2508</span>&#160;  }</div><div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>&#160;</div><div class="line"><a name="l02511"></a><span class="lineno"> 2511</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02512"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94b3800ead72ed432b76ef4a52423a9f"> 2512</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94b3800ead72ed432b76ef4a52423a9f">add_pointer_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#affeae7791be815ff2e0c99c60b079dab">LongIndex</a> offset) {</div><div class="line"><a name="l02513"></a><span class="lineno"> 2513</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(offset);</div><div class="line"><a name="l02514"></a><span class="lineno"> 2514</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>&#160;  }</div><div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>&#160;</div><div class="line"><a name="l02518"></a><span class="lineno"> 2518</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02519"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0d57f2074344f799ea1047c3ca41e5b5"> 2519</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp;<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0d57f2074344f799ea1047c3ca41e5b5">add_tile_offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02520"></a><span class="lineno"> 2520</span>&#160;</div><div class="line"><a name="l02521"></a><span class="lineno"> 2521</span>&#160;    ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">add_coord_offset</a>(tile_offset * <a class="code" href="namespacecutlass.html#a7419519fa453a121dfa5f26bf87318d9">make_Coord</a>(Shape::kRow, Shape::kColumn));</div><div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>&#160;</div><div class="line"><a name="l02523"></a><span class="lineno"> 2523</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02524"></a><span class="lineno"> 2524</span>&#160;  }</div><div class="line"><a name="l02525"></a><span class="lineno"> 2525</span>&#160;</div><div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02528"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a5143b72d5470049e8b879d2fab598b9b"> 2528</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a5143b72d5470049e8b879d2fab598b9b">operator++</a>() {</div><div class="line"><a name="l02529"></a><span class="lineno"> 2529</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l02530"></a><span class="lineno"> 2530</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02531"></a><span class="lineno"> 2531</span>&#160;  }</div><div class="line"><a name="l02532"></a><span class="lineno"> 2532</span>&#160;</div><div class="line"><a name="l02534"></a><span class="lineno"> 2534</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02535"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa6757114de97d47339a97caa1ff5d863"> 2535</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa6757114de97d47339a97caa1ff5d863">operator--</a>() {</div><div class="line"><a name="l02536"></a><span class="lineno"> 2536</span>&#160;    <span class="comment">// deliberate no-op</span></div><div class="line"><a name="l02537"></a><span class="lineno"> 2537</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02538"></a><span class="lineno"> 2538</span>&#160;  }</div><div class="line"><a name="l02539"></a><span class="lineno"> 2539</span>&#160;</div><div class="line"><a name="l02541"></a><span class="lineno"> 2541</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02542"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#afefe082ee98be3a0a7dfdadba702d58f"> 2542</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#afefe082ee98be3a0a7dfdadba702d58f">operator+=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02543"></a><span class="lineno"> 2543</span>&#160;    add_tile_offset(tile_offset);</div><div class="line"><a name="l02544"></a><span class="lineno"> 2544</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02545"></a><span class="lineno"> 2545</span>&#160;  }</div><div class="line"><a name="l02546"></a><span class="lineno"> 2546</span>&#160;</div><div class="line"><a name="l02548"></a><span class="lineno"> 2548</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02549"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa5e85b5ad8fcadd76dfc664c626875dc"> 2549</a></span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">MmaTensorOpAccumulatorTileIterator</a> &amp; <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa5e85b5ad8fcadd76dfc664c626875dc">operator-=</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset) {</div><div class="line"><a name="l02550"></a><span class="lineno"> 2550</span>&#160;    add_tile_offset(-tile_offset);</div><div class="line"><a name="l02551"></a><span class="lineno"> 2551</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l02552"></a><span class="lineno"> 2552</span>&#160;  }</div><div class="line"><a name="l02553"></a><span class="lineno"> 2553</span>&#160;</div><div class="line"><a name="l02555"></a><span class="lineno"> 2555</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02556"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0e1da365b37245f7cddf42b140cfcfed"> 2556</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0e1da365b37245f7cddf42b140cfcfed">load</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l02557"></a><span class="lineno"> 2557</span>&#160;    load_with_pointer_offset(frag, 0);</div><div class="line"><a name="l02558"></a><span class="lineno"> 2558</span>&#160;  }</div><div class="line"><a name="l02559"></a><span class="lineno"> 2559</span>&#160;</div><div class="line"><a name="l02561"></a><span class="lineno"> 2561</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02562"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94cf75f2354661fd5f7682f37ba79177"> 2562</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94cf75f2354661fd5f7682f37ba79177">load_with_pointer_offset</a>(</div><div class="line"><a name="l02563"></a><span class="lineno"> 2563</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02564"></a><span class="lineno"> 2564</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02565"></a><span class="lineno"> 2565</span>&#160;  </div><div class="line"><a name="l02566"></a><span class="lineno"> 2566</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l02567"></a><span class="lineno"> 2567</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l02568"></a><span class="lineno"> 2568</span>&#160;</div><div class="line"><a name="l02569"></a><span class="lineno"> 2569</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a>* frag_ptr = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> *<span class="keyword">&gt;</span>(&amp;frag);</div><div class="line"><a name="l02570"></a><span class="lineno"> 2570</span>&#160;</div><div class="line"><a name="l02571"></a><span class="lineno"> 2571</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02572"></a><span class="lineno"> 2572</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_n = 0; mma_n &lt; Policy::MmaIterations::kColumn; ++mma_n) {</div><div class="line"><a name="l02573"></a><span class="lineno"> 2573</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02574"></a><span class="lineno"> 2574</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_m = 0; mma_m &lt; Policy::MmaIterations::kRow; ++mma_m) {</div><div class="line"><a name="l02575"></a><span class="lineno"> 2575</span>&#160;        <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM;</div><div class="line"><a name="l02576"></a><span class="lineno"> 2576</span>&#160;        <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN;</div><div class="line"><a name="l02577"></a><span class="lineno"> 2577</span>&#160;</div><div class="line"><a name="l02578"></a><span class="lineno"> 2578</span>&#160;        <span class="keywordtype">int</span> idx = mma_m + mma_n * Policy::MmaIterations::kRow;</div><div class="line"><a name="l02579"></a><span class="lineno"> 2579</span>&#160;</div><div class="line"><a name="l02580"></a><span class="lineno"> 2580</span>&#160;        <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a>* access_ptr = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> *<span class="keyword">&gt;</span>(offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>() +</div><div class="line"><a name="l02581"></a><span class="lineno"> 2581</span>&#160;          offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a>(accum_m, accum_n)));</div><div class="line"><a name="l02582"></a><span class="lineno"> 2582</span>&#160;</div><div class="line"><a name="l02583"></a><span class="lineno"> 2583</span>&#160;        frag_ptr[idx] = access_ptr[0];</div><div class="line"><a name="l02584"></a><span class="lineno"> 2584</span>&#160;      }</div><div class="line"><a name="l02585"></a><span class="lineno"> 2585</span>&#160;    }</div><div class="line"><a name="l02586"></a><span class="lineno"> 2586</span>&#160;  }</div><div class="line"><a name="l02587"></a><span class="lineno"> 2587</span>&#160;</div><div class="line"><a name="l02589"></a><span class="lineno"> 2589</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02590"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aae461549926e9f040e3376d709122682"> 2590</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aae461549926e9f040e3376d709122682">load_with_byte_offset</a>(</div><div class="line"><a name="l02591"></a><span class="lineno"> 2591</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02592"></a><span class="lineno"> 2592</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02593"></a><span class="lineno"> 2593</span>&#160;</div><div class="line"><a name="l02594"></a><span class="lineno"> 2594</span>&#160;    load_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02595"></a><span class="lineno"> 2595</span>&#160;  }</div><div class="line"><a name="l02596"></a><span class="lineno"> 2596</span>&#160;</div><div class="line"><a name="l02598"></a><span class="lineno"> 2598</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02599"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a6768a9d602167ba3cccadb86f3003c06"> 2599</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a6768a9d602167ba3cccadb86f3003c06">load</a>(</div><div class="line"><a name="l02600"></a><span class="lineno"> 2600</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02602"></a><span class="lineno"> 2602</span>&#160;</div><div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>&#160;    load(frag, tile_offset, 0);</div><div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>&#160;  }</div><div class="line"><a name="l02605"></a><span class="lineno"> 2605</span>&#160;</div><div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02608"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae001cbba53a2df7684b048814c64e576"> 2608</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae001cbba53a2df7684b048814c64e576">load</a>(</div><div class="line"><a name="l02609"></a><span class="lineno"> 2609</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02610"></a><span class="lineno"> 2610</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,             </div><div class="line"><a name="l02611"></a><span class="lineno"> 2611</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>&#160;</div><div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>&#160;    load_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02614"></a><span class="lineno"> 2614</span>&#160;  }</div><div class="line"><a name="l02615"></a><span class="lineno"> 2615</span>&#160;</div><div class="line"><a name="l02617"></a><span class="lineno"> 2617</span>&#160;  <a class="code" href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="line"><a name="l02618"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaa2a193ee64ea10f76e21692f55570f0"> 2618</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaa2a193ee64ea10f76e21692f55570f0">store</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> <span class="keyword">const</span> &amp;frag)<span class="keyword"> const </span>{</div><div class="line"><a name="l02619"></a><span class="lineno"> 2619</span>&#160;    store_with_pointer_offset(frag, 0);</div><div class="line"><a name="l02620"></a><span class="lineno"> 2620</span>&#160;  }</div><div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>&#160;</div><div class="line"><a name="l02623"></a><span class="lineno"> 2623</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02624"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae8e8ffd03b9d6b239f6406d4278ad9e4"> 2624</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae8e8ffd03b9d6b239f6406d4278ad9e4">store_with_pointer_offset</a>(</div><div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02626"></a><span class="lineno"> 2626</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> pointer_offset)<span class="keyword"> const </span>{               </div><div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>&#160;  </div><div class="line"><a name="l02628"></a><span class="lineno"> 2628</span>&#160;    <a class="code" href="classcutlass_1_1TensorRef.html">TensorRef</a> offset_ref(ref_);</div><div class="line"><a name="l02629"></a><span class="lineno"> 2629</span>&#160;    offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">add_pointer_offset</a>(pointer_offset);</div><div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>&#160;</div><div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> <span class="keyword">const</span> *frag_ptr = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> const*<span class="keyword">&gt;</span>(&amp;frag);</div><div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>&#160;</div><div class="line"><a name="l02633"></a><span class="lineno"> 2633</span>&#160;    <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02634"></a><span class="lineno"> 2634</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_n = 0; mma_n &lt; Policy::MmaIterations::kColumn; ++mma_n) {</div><div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>&#160;      <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l02636"></a><span class="lineno"> 2636</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> mma_m = 0; mma_m &lt; Policy::MmaIterations::kRow; ++mma_m) {</div><div class="line"><a name="l02637"></a><span class="lineno"> 2637</span>&#160;        <span class="keywordtype">int</span> accum_m = mma_m * InstructionShape::kM;</div><div class="line"><a name="l02638"></a><span class="lineno"> 2638</span>&#160;        <span class="keywordtype">int</span> accum_n = mma_n * InstructionShape::kN;</div><div class="line"><a name="l02639"></a><span class="lineno"> 2639</span>&#160;</div><div class="line"><a name="l02640"></a><span class="lineno"> 2640</span>&#160;        <span class="keywordtype">int</span> idx = mma_m + mma_n * Policy::MmaIterations::kRow;</div><div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>&#160;</div><div class="line"><a name="l02642"></a><span class="lineno"> 2642</span>&#160;  <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a>* access_ptr = <span class="keyword">reinterpret_cast&lt;</span><a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">AccessType</a> *<span class="keyword">&gt;</span>(offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">data</a>() +</div><div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>&#160;         offset_ref.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(<a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a>(accum_m, accum_n)));</div><div class="line"><a name="l02644"></a><span class="lineno"> 2644</span>&#160;</div><div class="line"><a name="l02645"></a><span class="lineno"> 2645</span>&#160;        access_ptr[0] = frag_ptr[idx];         </div><div class="line"><a name="l02646"></a><span class="lineno"> 2646</span>&#160;      }</div><div class="line"><a name="l02647"></a><span class="lineno"> 2647</span>&#160;    }</div><div class="line"><a name="l02648"></a><span class="lineno"> 2648</span>&#160;  }</div><div class="line"><a name="l02649"></a><span class="lineno"> 2649</span>&#160;</div><div class="line"><a name="l02651"></a><span class="lineno"> 2651</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02652"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7fcc6c65b4c81f867ad80a08be6855b9"> 2652</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7fcc6c65b4c81f867ad80a08be6855b9">store_with_byte_offset</a>(</div><div class="line"><a name="l02653"></a><span class="lineno"> 2653</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> <span class="keyword">const</span> &amp;frag,                       </div><div class="line"><a name="l02654"></a><span class="lineno"> 2654</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> byte_offset)<span class="keyword"> const </span>{                  </div><div class="line"><a name="l02655"></a><span class="lineno"> 2655</span>&#160;</div><div class="line"><a name="l02656"></a><span class="lineno"> 2656</span>&#160;    store_with_pointer_offset(byte_offset / <span class="keyword">sizeof</span>(Element));</div><div class="line"><a name="l02657"></a><span class="lineno"> 2657</span>&#160;  }</div><div class="line"><a name="l02658"></a><span class="lineno"> 2658</span>&#160;</div><div class="line"><a name="l02660"></a><span class="lineno"> 2660</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02661"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a9b19b00acd8734d593c79982a934e93c"> 2661</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a9b19b00acd8734d593c79982a934e93c">store</a>(</div><div class="line"><a name="l02662"></a><span class="lineno"> 2662</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> &amp;frag,                             </div><div class="line"><a name="l02663"></a><span class="lineno"> 2663</span>&#160;    <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset)<span class="keyword"> const </span>{     </div><div class="line"><a name="l02664"></a><span class="lineno"> 2664</span>&#160;</div><div class="line"><a name="l02665"></a><span class="lineno"> 2665</span>&#160;    store(frag, tile_offset, 0);</div><div class="line"><a name="l02666"></a><span class="lineno"> 2666</span>&#160;  }</div><div class="line"><a name="l02667"></a><span class="lineno"> 2667</span>&#160;</div><div class="line"><a name="l02669"></a><span class="lineno"> 2669</span>&#160;  CUTLASS_DEVICE</div><div class="line"><a name="l02670"></a><span class="lineno"><a class="line" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7d87ebd6a241f7db7e3888a6f511a90c"> 2670</a></span>&#160;  <span class="keywordtype">void</span> <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7d87ebd6a241f7db7e3888a6f511a90c">store</a>(</div><div class="line"><a name="l02672"></a><span class="lineno"> 2672</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">Fragment</a> <span class="keyword">const</span> &amp;frag,</div><div class="line"><a name="l02674"></a><span class="lineno"> 2674</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">TensorCoord</a> <span class="keyword">const</span> &amp;tile_offset,</div><div class="line"><a name="l02676"></a><span class="lineno"> 2676</span>&#160;      <a class="code" href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">Index</a> pointer_offset)<span class="keyword"> const </span>{</div><div class="line"><a name="l02677"></a><span class="lineno"> 2677</span>&#160;    store_with_pointer_offset(frag, ref_.<a class="code" href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">offset</a>(tile_offset) + pointer_offset);</div><div class="line"><a name="l02678"></a><span class="lineno"> 2678</span>&#160;  }</div><div class="line"><a name="l02679"></a><span class="lineno"> 2679</span>&#160;};</div><div class="line"><a name="l02680"></a><span class="lineno"> 2680</span>&#160;</div><div class="line"><a name="l02682"></a><span class="lineno"> 2682</span>&#160;} <span class="comment">// namespace warp</span></div><div class="line"><a name="l02683"></a><span class="lineno"> 2683</span>&#160;} <span class="comment">// namespace gemm</span></div><div class="line"><a name="l02684"></a><span class="lineno"> 2684</span>&#160;} <span class="comment">// namespace cutlass</span></div><div class="line"><a name="l02685"></a><span class="lineno"> 2685</span>&#160;</div><div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ad8269a57d4abf11261086c3f5cde979b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad8269a57d4abf11261086c3f5cde979b">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::OpDelta</a></div><div class="ttdeci">OpDelta_ OpDelta</div><div class="ttdoc">Delta between *MMA operations (in units of *MMA operations, concept: MatrixShape) ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1836</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a546ea293ab08e4474731b3e6e61bc019"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a546ea293ab08e4474731b3e6e61bc019">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2119</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a2deff3a17ae49f6b0c6f7d46f3296144"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2deff3a17ae49f6b0c6f7d46f3296144">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1389</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a5729ea6986033389dae3e6a724292507"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a5729ea6986033389dae3e6a724292507">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1139</div></div>
<div class="ttc" id="structcutlass_1_1MatrixShape_html"><div class="ttname"><a href="structcutlass_1_1MatrixShape.html">cutlass::MatrixShape</a></div><div class="ttdoc">Describes the size of a matrix tile. </div><div class="ttdef"><b>Definition:</b> matrix_shape.h:42</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a42e843e212116c332aecd3468fa53a0e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a42e843e212116c332aecd3468fa53a0e">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1652</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ade94421981f93d1623a260ec253b09da"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ade94421981f93d1623a260ec253b09da">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1915</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a052283230cbfb19fdc57482b12e91429"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a052283230cbfb19fdc57482b12e91429">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Element</a></div><div class="ttdeci">Element_ Element</div><div class="ttdoc">Element type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:476</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_ab12387376473d0975cbf02f9d04a153c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab12387376473d0975cbf02f9d04a153c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1052</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a784a554c0b5d90d36e8df22df8e4d80c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a784a554c0b5d90d36e8df22df8e4d80c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2433</div></div>
<div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_aa3eecd0ea10efc45a6c11569a3e9d1b5"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa3eecd0ea10efc45a6c11569a3e9d1b5">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:483</div></div>
<div class="ttc" id="tensor__ref_8h_html"><div class="ttname"><a href="tensor__ref_8h.html">tensor_ref.h</a></div><div class="ttdoc">Defines a structure containing strides, bounds, and a pointer to tensor data. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_abe224b64e7ed23246e233d7a407efdc8"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abe224b64e7ed23246e233d7a407efdc8">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1514</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a0726a2e59e0eff3c40786d8712e47776"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a0726a2e59e0eff3c40786d8712e47776">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1259</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_ace4698285e3ccb3d680e721d45c3604a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ace4698285e3ccb3d680e721d45c3604a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:966</div></div>
<div class="ttc" id="tensor__op__multiplicand__sm75_8h_html"><div class="ttname"><a href="tensor__op__multiplicand__sm75_8h.html">tensor_op_multiplicand_sm75.h</a></div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a14693f854e28e9f39e46843c5f805767"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a14693f854e28e9f39e46843c5f805767">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:223</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_adb4fa15e29e8f14136d9f6a9826bbfd2"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#adb4fa15e29e8f14136d9f6a9826bbfd2">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:569</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a7407a4b2ac07e96c39c1e53aeb76a594"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a7407a4b2ac07e96c39c1e53aeb76a594">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1207</div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCrosswise_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCrosswise.html">cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:734</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_ab2bef766745fa8bfac1279a038b5bf23"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2bef766745fa8bfac1279a038b5bf23">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:257</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_ada9807d73db23e2388054d3a89e6cd35"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ada9807d73db23e2388054d3a89e6cd35">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2496</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_af6507b45143ec47c96e03c578af82e33"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#af6507b45143ec47c96e03c578af82e33">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Stores a fragment to memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2073</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a9b19b00acd8734d593c79982a934e93c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a9b19b00acd8734d593c79982a934e93c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Stores a fragment to memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2661</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_ac6dc64ff8af8291455978f9fd168c6fc"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac6dc64ff8af8291455978f9fd168c6fc">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2236</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_ac7db3ca62ab1dfe0d3ea08bcadbc9352"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#ac7db3ca62ab1dfe0d3ea08bcadbc9352">cutlass::TensorRef::data</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Element * data() const </div><div class="ttdoc">Returns the pointer to referenced data. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:254</div></div>
<div class="ttc" id="structcutlass_1_1platform_1_1is__same_html"><div class="ttname"><a href="structcutlass_1_1platform_1_1is__same.html">cutlass::platform::is_same</a></div><div class="ttdoc">std::is_same (false specialization) </div><div class="ttdef"><b>Definition:</b> platform.h:394</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a2f1d8841e730498582a557e73c1467fe"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a2f1d8841e730498582a557e73c1467fe">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:765</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_ae4af2d212abc11a8cf1a97d47b230f00"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ae4af2d212abc11a8cf1a97d47b230f00">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1163</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ab49df5f2b62c1dbc7533d1ad36881d5c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab49df5f2b62c1dbc7533d1ad36881d5c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:773</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a5a76314f07d7a5ddeed7a566228acc4d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5a76314f07d7a5ddeed7a566228acc4d">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2296</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a9e0746c3f1115c0669dc9d065c50c5f8"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9e0746c3f1115c0669dc9d065c50c5f8">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1845</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aa1789d85a3ac04dd71be4bddff2dab5a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa1789d85a3ac04dd71be4bddff2dab5a">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment const &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2381</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_abed4efcbfe0634ccaeae64eef124cceb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#abed4efcbfe0634ccaeae64eef124cceb">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1026</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_aed04d00e3dd336bdfc9eff39e1123861"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aed04d00e3dd336bdfc9eff39e1123861">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:219</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ab0919a07c2d37fae0679481ef4ed8138"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ab0919a07c2d37fae0679481ef4ed8138">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:732</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a8da3cde971d4dd1beb123645b59e90db"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a8da3cde971d4dd1beb123645b59e90db">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:328</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_aa711fab987df637da35e00d655dcaf65"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa711fab987df637da35e00d655dcaf65">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:321</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_affd5c6e12f2fc9c00ec08d43e8f8d2f6"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#affd5c6e12f2fc9c00ec08d43e8f8d2f6">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1952</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_af8c5a6fe57db046155a8145fe386dbc1"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#af8c5a6fe57db046155a8145fe386dbc1">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:408</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a3ce87fe4f5ea64612fe20bc97dcab01d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3ce87fe4f5ea64612fe20bc97dcab01d">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1418</div></div>
<div class="ttc" id="namespacecutlass_html_a7419519fa453a121dfa5f26bf87318d9"><div class="ttname"><a href="namespacecutlass.html#a7419519fa453a121dfa5f26bf87318d9">cutlass::make_Coord</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Coord&lt; 1 &gt; make_Coord(int _0)</div><div class="ttdoc">Helper to make a 2-element coordinate. </div><div class="ttdef"><b>Definition:</b> coord.h:387</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ab44ddbcd150470e1d234b2138ee1e8ef"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ab44ddbcd150470e1d234b2138ee1e8ef">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1692</div></div>
<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6">cutlass::gemm::Operand</a></div><div class="ttdeci">Operand</div><div class="ttdoc">GEMM operand enumeration: D = A * B + C. </div><div class="ttdef"><b>Definition:</b> include/cutlass/gemm/gemm.h:39</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a86ef850cea2f61213ca9aa53a2c78ff1"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a86ef850cea2f61213ca9aa53a2c78ff1">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment const &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2082</div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCongruous_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1ColumnMajorTensorOpMultiplicandCongruous.html">cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:422</div></div>
<div class="ttc" id="memory__sm75_8h_html"><div class="ttname"><a href="memory__sm75_8h.html">memory_sm75.h</a></div><div class="ttdoc">Architecture-specific operators on memory added for SM75. </div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCrosswise_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCrosswise.html">cutlass::layout::RowMajorTensorOpMultiplicandCrosswise</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:835</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a14bf57fe01b0419ef0a6b17730819c65"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a14bf57fe01b0419ef0a6b17730819c65">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1279</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a5afb883b6fd6b897ff852ab93c6ba871"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a5afb883b6fd6b897ff852ab93c6ba871">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1616</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_aaf694dd4b0520ff3430a012777f350bc"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aaf694dd4b0520ff3430a012777f350bc">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:872</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a33b7e2083273b6ecaacf7a98045e5ad7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a33b7e2083273b6ecaacf7a98045e5ad7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1224</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a9e8bb224bd9d307c1e8c7b0b898c3912"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9e8bb224bd9d307c1e8c7b0b898c3912">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:293</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a790515ce517729945be3a05828ca5882"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a790515ce517729945be3a05828ca5882">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:840</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a5804aaa9ff4b99b8e1baa0355d34e0c1"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5804aaa9ff4b99b8e1baa0355d34e0c1">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1965</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a32d9d7875ad2a5fbb0281115b11ebce9"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a32d9d7875ad2a5fbb0281115b11ebce9">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1386</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a3fff7e20df1a937e44aef89e468ef281"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a3fff7e20df1a937e44aef89e468ef281">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1922</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ad48f385d6822485184461d82bd70d4de"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad48f385d6822485184461d82bd70d4de">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1945</div></div>
<div class="ttc" id="include_2cutlass_2gemm_2gemm_8h_html"><div class="ttname"><a href="include_2cutlass_2gemm_2gemm_8h.html">gemm.h</a></div><div class="ttdoc">Defines common types used for all GEMM-like operators. </div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1TensorOpMultiplicandCongruous.html">cutlass::layout::TensorOpMultiplicandCongruous</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:213</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_aafd0dda75aa9b12d787a8aca0e48c4df"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aafd0dda75aa9b12d787a8aca0e48c4df">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:432</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ad9ac79132faaf9d6913e13915f1d7cde"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9ac79132faaf9d6913e13915f1d7cde">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1648</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ad207cf1fa0534c8af6d571df376d8512"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad207cf1fa0534c8af6d571df376d8512">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1583</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aef34e6d38c9039cb9fecb364186e1741"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aef34e6d38c9039cb9fecb364186e1741">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2143</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a0b99108d7d2ac1b2047c3d6ea51a6423"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a0b99108d7d2ac1b2047c3d6ea51a6423">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1833</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ac698bc8cd44572e1f3ee52771fb2cefb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ac698bc8cd44572e1f3ee52771fb2cefb">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1683</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a94cf75f2354661fd5f7682f37ba79177"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94cf75f2354661fd5f7682f37ba79177">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2562</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ad0e1edd1608df393c451b9ac6bd079de"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad0e1edd1608df393c451b9ac6bd079de">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:816</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ad70395a1fbd33b034888f797e1bb8e30"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ad70395a1fbd33b034888f797e1bb8e30">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::store_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_pointer_offset(Fragment const &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2031</div></div>
<div class="ttc" id="platform_8h_html"><div class="ttname"><a href="platform_8h.html">platform.h</a></div><div class="ttdoc">C++ features that may be otherwise unimplemented for CUDA device functions. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_af415b1bda869f2ef506c6a92dafc5829"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af415b1bda869f2ef506c6a92dafc5829">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2146</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a570f020d67995c1a7232e14ec07e3b0c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a570f020d67995c1a7232e14ec07e3b0c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2263</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a85a6af3ca6d0768de87abfb05be3172f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a85a6af3ca6d0768de87abfb05be3172f">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:726</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ad657ba5ffa2eb7c80c4328a47783e67a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad657ba5ffa2eb7c80c4328a47783e67a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:809</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_af8d0bb15e6c967e41c175d7989c728b2"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#af8d0bb15e6c967e41c175d7989c728b2">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2243</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a9b33490455b2ec60311e97712a5ae7da"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9b33490455b2ec60311e97712a5ae7da">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1895</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ac0806ad1ce257502ba7a2c0b580b117b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ac0806ad1ce257502ba7a2c0b580b117b">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1884</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ad44b3c1bfee9f5a8ddc962e78d81aefb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad44b3c1bfee9f5a8ddc962e78d81aefb">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:860</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a1a46c311062f11a9eb5a4f34407f022b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1a46c311062f11a9eb5a4f34407f022b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:599</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a97d09b2ad300996739ff4d1935804aaa"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a97d09b2ad300996739ff4d1935804aaa">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1216</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a6ebdb3095e18ac34da6e7947fc050d26"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a6ebdb3095e18ac34da6e7947fc050d26">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:609</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a8514fa821eb580b6b80c33fc32c6b197"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a8514fa821eb580b6b80c33fc32c6b197">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1757</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a085b222207880b579b8ffa91c905e071"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a085b222207880b579b8ffa91c905e071">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2229</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_ab273a94817606b8bdbc714a7964bd95b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab273a94817606b8bdbc714a7964bd95b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the opposite of the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:312</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a0d57f2074344f799ea1047c3ca41e5b5"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0d57f2074344f799ea1047c3ca41e5b5">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2519</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a3201247518a0b500753b719c92517768"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a3201247518a0b500753b719c92517768">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1546</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ad91c3ff6512ec6f63dac11af36f553cb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ad91c3ff6512ec6f63dac11af36f553cb">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:714</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a4bed879c428963070de8ffbdc5d6e4f9"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a4bed879c428963070de8ffbdc5d6e4f9">cutlass::TensorRef::add_coord_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE TensorRef &amp; add_coord_offset(TensorCoord const &amp;coord)</div><div class="ttdoc">Adds an offset to each pointer. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:326</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a7a6014e499e20aa8f4134c0dded53d09"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7a6014e499e20aa8f4134c0dded53d09">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:641</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_aa061b3786066f1fbde3e6c993e2dec6c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#aa061b3786066f1fbde3e6c993e2dec6c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:266</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a0e1da365b37245f7cddf42b140cfcfed"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a0e1da365b37245f7cddf42b140cfcfed">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2556</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a58c1c86c36a821bdbba0e7bbe59e79ec"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a58c1c86c36a821bdbba0e7bbe59e79ec">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1723</div></div>
<div class="ttc" id="classcutlass_1_1layout_1_1ColumnMajor_html"><div class="ttname"><a href="classcutlass_1_1layout_1_1ColumnMajor.html">cutlass::layout::ColumnMajor</a></div><div class="ttdoc">Mapping function for column-major matrices. </div><div class="ttdef"><b>Definition:</b> layout/matrix.h:142</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_abba62827ecc9247b59e1d03898c5feb2"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#abba62827ecc9247b59e1d03898c5feb2">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1938</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a78c667580cfda7d22e63e98dcf5789c4"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a78c667580cfda7d22e63e98dcf5789c4">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2445</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aa177f1e6b921b9d1b423ebc05a1f2e0e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aa177f1e6b921b9d1b423ebc05a1f2e0e">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2197</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a6c481c9a25374ae10fc47e17d5736b89"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a6c481c9a25374ae10fc47e17d5736b89">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:830</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a5143b72d5470049e8b879d2fab598b9b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a5143b72d5470049e8b879d2fab598b9b">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2528</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_af05eb3e5ea74cdeadfeda004b42ce8a1"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#af05eb3e5ea74cdeadfeda004b42ce8a1">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:782</div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1PitchLinearShape_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1PitchLinearShape.html">cutlass::layout::PitchLinearShape</a></div><div class="ttdoc">Template defining a shape used by pitch-linear operators. </div><div class="ttdef"><b>Definition:</b> pitch_linear.h:43</div></div>
<div class="ttc" id="array_8h_html"><div class="ttname"><a href="array_8h.html">array.h</a></div><div class="ttdoc">Statically sized array of elements that accommodates all CUTLASS-supported numeric types and is safe ...</div></div>
<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6af73b7a14626c25aa554e2437ea3fc1df"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6af73b7a14626c25aa554e2437ea3fc1df">cutlass::gemm::Operand::kC</a></div><div class="ttdoc">B multiplicand. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ad8b8e35294c22e6b18be337ae3544c76"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad8b8e35294c22e6b18be337ae3544c76">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1666</div></div>
<div class="ttc" id="cutlass_8h_html_a4b1c9f25ab6eaa25e1f2258dd63e6ce4"><div class="ttname"><a href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="ttdeci">#define CUTLASS_PRAGMA_UNROLL</div><div class="ttdef"><b>Definition:</b> cutlass.h:110</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a258a2278561191525ebfab2e6ff93d8f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a258a2278561191525ebfab2e6ff93d8f">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:202</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a6d44b68261394c954c3667a061c0d91b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6d44b68261394c954c3667a061c0d91b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1503</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a6f96ec999bbddffcaca1a31aa31e9708"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a6f96ec999bbddffcaca1a31aa31e9708">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1483</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a9f16e361268ea077a08a0182984db261"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a9f16e361268ea077a08a0182984db261">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2220</div></div>
<div class="ttc" id="tensor_8h_html"><div class="ttname"><a href="tensor_8h.html">tensor.h</a></div><div class="ttdoc">Defines layout functions used by TensorRef and derived classes for common 4-D and 5-D tensor formats...</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a0f61bf6c060f3e0a471608f45b3580c3"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a0f61bf6c060f3e0a471608f45b3580c3">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1776</div></div>
<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a30f767aa191cd5d261e767fd78393607">cutlass::gemm::Operand::kA</a></div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ab240ac0cbcdf7d654f5c37fc0f726f65"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab240ac0cbcdf7d654f5c37fc0f726f65">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:466</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a1e951937f4ef558a694519404d757bdb"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a1e951937f4ef558a694519404d757bdb">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::OpDelta</a></div><div class="ttdeci">OpDelta_ OpDelta</div><div class="ttdoc">Delta between *MMA operations (in units of *MMA operations, concept: MatrixShape) ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2436</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a9f5db55c060463a11a052280a950bf9f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a9f5db55c060463a11a052280a950bf9f">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1851</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a7fcc6c65b4c81f867ad80a08be6855b9"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7fcc6c65b4c81f867ad80a08be6855b9">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::store_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_byte_offset(Fragment const &amp;frag, Index byte_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2652</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a5b36b747c47da28a51a5ec94fa51edef"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a5b36b747c47da28a51a5ec94fa51edef">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2193</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a191e88bc0fb310be655d700e937ab97c"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a191e88bc0fb310be655d700e937ab97c">cutlass::TensorRef::stride</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Stride stride() const </div><div class="ttdoc">Returns the layout object&amp;#39;s stride vector. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:277</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a72d7ffbb1e1558425e1e7370e2e3ec48"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a72d7ffbb1e1558425e1e7370e2e3ec48">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Stores a fragment to memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2372</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a5c88fe11bac5ea0b60f3c73f4dc8b758"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5c88fe11bac5ea0b60f3c73f4dc8b758">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1427</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_ace218cdb46555a46bd71dbdfc2c317c1"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#ace218cdb46555a46bd71dbdfc2c317c1">cutlass::TensorRef::TensorCoord</a></div><div class="ttdeci">typename Layout::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate in logical tensor space. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:171</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ae9b9762870c51eadb90c795c65d638b0"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae9b9762870c51eadb90c795c65d638b0">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void store(Fragment const &amp;frag) const </div><div class="ttdoc">Stores a fragment to memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2025</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ab92dd8e4707aa642654935e4ab9c6ae7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab92dd8e4707aa642654935e4ab9c6ae7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:534</div></div>
<div class="ttc" id="matrix__shape_8h_html"><div class="ttname"><a href="matrix__shape_8h.html">matrix_shape.h</a></div><div class="ttdoc">Defines a Shape template for matrix tiles. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a1e1b513870c418a8430cfecd56b60b98"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1e1b513870c418a8430cfecd56b60b98">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:386</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a82b17c0d55556b72697597851644bb53"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a82b17c0d55556b72697597851644bb53">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1527</div></div>
<div class="ttc" id="structcutlass_1_1sizeof__bits_html"><div class="ttname"><a href="structcutlass_1_1sizeof__bits.html">cutlass::sizeof_bits</a></div><div class="ttdoc">Defines the size of an element in bits. </div><div class="ttdef"><b>Definition:</b> numeric_types.h:42</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a15ab4cedbfb44dc89b7dcf69bdd9b5b4"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a15ab4cedbfb44dc89b7dcf69bdd9b5b4">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:342</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_aac602e347a7e35680d0a0dd1b9e82951"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aac602e347a7e35680d0a0dd1b9e82951">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1291</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a7f9e9b46f9dc826b7f677bcd17bcfe66"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a7f9e9b46f9dc826b7f677bcd17bcfe66">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1997</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_adfcfe12e980652302eddabcf06911208"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#adfcfe12e980652302eddabcf06911208">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1471</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_html"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator.html">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1794</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_ad5154742e24c958288b0f52544aaaa68"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ad5154742e24c958288b0f52544aaaa68">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1409</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_abb80a20c60f1c8702a217cc56fa0b348"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#abb80a20c60f1c8702a217cc56fa0b348">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:750</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a47b254c2c94b869ca7e6f73d98e2a155"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a47b254c2c94b869ca7e6f73d98e2a155">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1622</div></div>
<div class="ttc" id="platform_8h_html_ab979d9d4b4923f7c54d6caa6e1a61936"><div class="ttname"><a href="platform_8h.html#ab979d9d4b4923f7c54d6caa6e1a61936">nullptr</a></div><div class="ttdeci">#define nullptr</div><div class="ttdoc">nullptr </div><div class="ttdef"><b>Definition:</b> platform.h:144</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a283aff9bb995527e3a65752a3e2d8fe6"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a283aff9bb995527e3a65752a3e2d8fe6">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1657</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html"><div class="ttname"><a href="classcutlass_1_1TensorRef.html">cutlass::TensorRef&lt; Element, Layout &gt;</a></div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a459d61e80b72846e8a096b5c93e3b7a8"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a459d61e80b72846e8a096b5c93e3b7a8">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:761</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_aa851acf5c1e2a7ffa24526eebb347c1f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#aa851acf5c1e2a7ffa24526eebb347c1f">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1228</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aa5e85b5ad8fcadd76dfc664c626875dc"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa5e85b5ad8fcadd76dfc664c626875dc">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2549</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aaa2a193ee64ea10f76e21692f55570f0"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaa2a193ee64ea10f76e21692f55570f0">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void store(Fragment const &amp;frag) const </div><div class="ttdoc">Stores a fragment to memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2618</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_ae6d98630ac77ae55f55281d7a9055b66"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#ae6d98630ac77ae55f55281d7a9055b66">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:823</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_aaad33f64f25dbcca8a34f577ad247595"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#aaad33f64f25dbcca8a34f577ad247595">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1675</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a5d008e10ed2dc1572a2d9392a41d4dac"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a5d008e10ed2dc1572a2d9392a41d4dac">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::store_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_byte_offset(Fragment const &amp;frag, Index byte_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2064</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_aee6eda1ac83a4545e0220036871e8ab2"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aee6eda1ac83a4545e0220036871e8ab2">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1436</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a7ffcc9310bf82c2885e1e623e4a708aa"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a7ffcc9310bf82c2885e1e623e4a708aa">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:107</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_acce80cd5cb5ab6c23795a8748c427610"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#acce80cd5cb5ab6c23795a8748c427610">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:791</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a3e29a84e9e4f4893492f7e200355087e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a3e29a84e9e4f4893492f7e200355087e">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:138</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a4976d5d69018094eddecb44de711343e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a4976d5d69018094eddecb44de711343e">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1373</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ae7697f2e94df8d38463f136887d77533"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae7697f2e94df8d38463f136887d77533">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:662</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aa80ed8a40b27d0d0e5b5f8577fc24436"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa80ed8a40b27d0d0e5b5f8577fc24436">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2421</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_ab4334bc63da845c9606103e04f389a6d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#ab4334bc63da845c9606103e04f389a6d">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:969</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_ac937a12e2f235d6465ecbf2142cc76cd"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ac937a12e2f235d6465ecbf2142cc76cd">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::OpDelta</a></div><div class="ttdeci">OpDelta_ OpDelta</div><div class="ttdoc">Delta between *MMA operations (in units of *MMA operations, concept: MatrixShape) ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2134</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a909bd811645c74d84837ed21c3318b96"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a909bd811645c74d84837ed21c3318b96">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1316</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_aacfc1f7f194fad9371391134b2acf801"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aacfc1f7f194fad9371391134b2acf801">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:560</div></div>
<div class="ttc" id="cutlass_8h_html_a28c2443a142676d3d71effdae1a986b1"><div class="ttname"><a href="cutlass_8h.html#a28c2443a142676d3d71effdae1a986b1">CUTLASS_HOST_DEVICE</a></div><div class="ttdeci">#define CUTLASS_HOST_DEVICE</div><div class="ttdef"><b>Definition:</b> cutlass.h:89</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_aacb661cde511fb812d82d0490c936195"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#aacb661cde511fb812d82d0490c936195">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::set_kgroup_index</a></div><div class="ttdeci">CUTLASS_DEVICE void set_kgroup_index(int k_group)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:893</div></div>
<div class="ttc" id="numeric__types_8h_html"><div class="ttname"><a href="numeric__types_8h.html">numeric_types.h</a></div><div class="ttdoc">Top-level include for all CUTLASS numeric types. </div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a4166ac2a0754574ac21d5d57d74f34e5"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a4166ac2a0754574ac21d5d57d74f34e5">cutlass::TensorRef::offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE LongIndex offset(TensorCoord const &amp;coord) const </div><div class="ttdoc">Computes the offset of an index from the origin of the tensor. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:301</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_html"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator.html">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:75</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a94b3800ead72ed432b76ef4a52423a9f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a94b3800ead72ed432b76ef4a52423a9f">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2512</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a847a66cca3fbafbd3d4cce72a9ad2440"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a847a66cca3fbafbd3d4cce72a9ad2440">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:930</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a6f687d886a3e6eb106bfd59298e6f5c6"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a6f687d886a3e6eb106bfd59298e6f5c6">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:141</div></div>
<div class="ttc" id="platform_8h_html_adde4c9ea91b753491851361a4198c009"><div class="ttname"><a href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a></div><div class="ttdeci">#define static_assert(__e, __m)</div><div class="ttdef"><b>Definition:</b> platform.h:153</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a6768a9d602167ba3cccadb86f3003c06"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a6768a9d602167ba3cccadb86f3003c06">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2599</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a0b3b6e84e68211479165f6bfce96421d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a0b3b6e84e68211479165f6bfce96421d">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1493</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a233b7f950eb27053b5c596dbd0ee7eb6"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a233b7f950eb27053b5c596dbd0ee7eb6">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1959</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ada65ee7584604de9a688d88838399809"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ada65ee7584604de9a688d88838399809">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1931</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_ae001cbba53a2df7684b048814c64e576"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae001cbba53a2df7684b048814c64e576">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2608</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_aa0317bb349e4b16873cfe51dfa748519"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#aa0317bb349e4b16873cfe51dfa748519">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator++</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator++()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1445</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_ab319010cfbb0e20723c0fbdefac6a10e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#ab319010cfbb0e20723c0fbdefac6a10e">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1453</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_ae68482e62a32c98bb5c2aaf64a835586"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae68482e62a32c98bb5c2aaf64a835586">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::store_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_byte_offset(Fragment const &amp;frag, Index byte_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2363</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a4a5c6c8dec5efca214619756b3e38bfc"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a4a5c6c8dec5efca214619756b3e38bfc">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2305</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a8379144007ec28f9b99ff85f255bed49"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a8379144007ec28f9b99ff85f255bed49">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:585</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a2229636a51c6233ee4f9de8a0f15107a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a2229636a51c6233ee4f9de8a0f15107a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: GemmShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:123</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ae008d65b6f163052d6f261004964dfd7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ae008d65b6f163052d6f261004964dfd7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:542</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a86cfe634c08dbf97d12b62eeaff1fa2c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a86cfe634c08dbf97d12b62eeaff1fa2c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:729</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a1bf4e5cf980f73ff62c0df8d6d2e99a9"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a1bf4e5cf980f73ff62c0df8d6d2e99a9">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1848</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a13030898f2eaab4b5d4136ff0932d649"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a13030898f2eaab4b5d4136ff0932d649">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1709</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a7f05dbc9436d93dc51401881e9d3b252"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a7f05dbc9436d93dc51401881e9d3b252">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:519</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_ad9e19bef825c4f9eb203ad22149a79a5"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#ad9e19bef825c4f9eb203ad22149a79a5">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1619</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ac9e271c881bf768a980f86a04c67932a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ac9e271c881bf768a980f86a04c67932a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Index</a></div><div class="ttdeci">typename TensorRef::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:495</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a87790289d78b1b515f95f5e81626a236"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a87790289d78b1b515f95f5e81626a236">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1422</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a11ec4b07a2132e647ca2ebe5112ce5ec"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a11ec4b07a2132e647ca2ebe5112ce5ec">cutlass::TensorRef::Index</a></div><div class="ttdeci">typename Layout::Index Index</div><div class="ttdoc">Index type. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:165</div></div>
<div class="ttc" id="classcutlass_1_1layout_1_1RowMajor_html"><div class="ttname"><a href="classcutlass_1_1layout_1_1RowMajor.html">cutlass::layout::RowMajor</a></div><div class="ttdoc">Mapping function for row-major matrices. </div><div class="ttdef"><b>Definition:</b> layout/matrix.h:50</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a1c344341137b6d501556dbbf29dc53ac"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a1c344341137b6d501556dbbf29dc53ac">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1744</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a63bfeacfdc5a1a13b1ae9a01e65ba3ee"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a63bfeacfdc5a1a13b1ae9a01e65ba3ee">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2015</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aabb62dc50c032e4691e6d96ea6740f12"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aabb62dc50c032e4691e6d96ea6740f12">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2131</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a3ff0b3e06a62a6d4d1d3aeb4bf491d87"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a3ff0b3e06a62a6d4d1d3aeb4bf491d87">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1269</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a30f749a5f6451b8acfb90e1eef5e529c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a30f749a5f6451b8acfb90e1eef5e529c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1821</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a276c1d33c1380292ac581eae6afe00f2"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a276c1d33c1380292ac581eae6afe00f2">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: GemmShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:950</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_ab01cd5a33f54ab40ffea40556a042329"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#ab01cd5a33f54ab40ffea40556a042329">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:530</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a8758907a1c9b1fcd00e7ece626d03b76"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a8758907a1c9b1fcd00e7ece626d03b76">cutlass::TensorRef::at</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE Reference at(TensorCoord const &amp;coord) const </div><div class="ttdoc">Returns a reference to the element at a given Coord. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:307</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a313942884867ffbe05c046a2ae577f7f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a313942884867ffbe05c046a2ae577f7f">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void store(Fragment const &amp;frag) const </div><div class="ttdoc">Stores a fragment to memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2324</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a9faeee6e6b7c8a8aaa0b60a47b93476b"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a9faeee6e6b7c8a8aaa0b60a47b93476b">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:376</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aaeee8d14c95678428d8d2ba36e76b9d0"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaeee8d14c95678428d8d2ba36e76b9d0">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2257</div></div>
<div class="ttc" id="layout_2matrix_8h_html"><div class="ttname"><a href="layout_2matrix_8h.html">matrix.h</a></div><div class="ttdoc">Defines layout functions used by TensorRef and derived classes. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a7d87ebd6a241f7db7e3888a6f511a90c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a7d87ebd6a241f7db7e3888a6f511a90c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::store</a></div><div class="ttdeci">CUTLASS_DEVICE void store(Fragment const &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2670</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_abc1e2caeaf199bb237021aedb568ff82"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#abc1e2caeaf199bb237021aedb568ff82">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1353</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_ab2fbe2cbd187897d82c4ad0de6cc6008"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#ab2fbe2cbd187897d82c4ad0de6cc6008">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:396</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a332174db47ba7103e8165861b1383b4a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a332174db47ba7103e8165861b1383b4a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Shape</a></div><div class="ttdeci">Shape_ Shape</div><div class="ttdoc">Shape of tile to load (concept: PitchLinearShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:697</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a14abb245ffc13842b281db8f72b71361"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a14abb245ffc13842b281db8f72b71361">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1701</div></div>
<div class="ttc" id="fast__math_8h_html"><div class="ttname"><a href="fast__math_8h.html">fast_math.h</a></div><div class="ttdoc">Math utilities. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a80210fe006f6058886d8aa53677af116"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a80210fe006f6058886d8aa53677af116">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1148</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_aae859de5fea22c7ee1653d9eabe0468d"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aae859de5fea22c7ee1653d9eabe0468d">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:578</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a4046a63c74343751da21c305e51a5cae"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a4046a63c74343751da21c305e51a5cae">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::AccessType</a></div><div class="ttdeci">Array&lt; Element, kElementsPerAccess &gt; AccessType</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2478</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a1d168c4b070f87a65bf900e7a63e14f3"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a1d168c4b070f87a65bf900e7a63e14f3">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:498</div></div>
<div class="ttc" id="pitch__linear_8h_html"><div class="ttname"><a href="pitch__linear_8h.html">pitch_linear.h</a></div><div class="ttdoc">Defines layout functions used by TensorRef and derived classes for pitch-linear memory. </div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1ColumnMajorInterleaved_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1ColumnMajorInterleaved.html">cutlass::layout::ColumnMajorInterleaved</a></div><div class="ttdef"><b>Definition:</b> layout/matrix.h:343</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_a6bbcd0e512915565cabfeccdb1b6417d"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#a6bbcd0e512915565cabfeccdb1b6417d">cutlass::TensorRef::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE TensorRef &amp; add_pointer_offset(LongIndex offset_)</div><div class="ttdoc">Adds an offset to each pointer. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:319</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_abe2b74533d91f56799cab0365af27fe5"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#abe2b74533d91f56799cab0365af27fe5">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1639</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a2d5b5e7e31f4c85df162d8bbd020b8ae"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a2d5b5e7e31f4c85df162d8bbd020b8ae">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:972</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_afde63a685ffcd99a9bbc1c9b6e121c9a"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#afde63a685ffcd99a9bbc1c9b6e121c9a">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1733</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a1be13f61b06e0f27e27b0b54349cac5c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1be13f61b06e0f27e27b0b54349cac5c">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:335</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a5bf6f7434406ae011baad51c8f6134d7"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a5bf6f7434406ae011baad51c8f6134d7">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1479</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_aaea5e34d1fd1a462103790268c6d549c"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#aaea5e34d1fd1a462103790268c6d549c">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::store_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_pointer_offset(Fragment const &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2330</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a2eb415e875f59697d8b38af6bfa540de"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a2eb415e875f59697d8b38af6bfa540de">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_pointer_offset(Fragment &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1713</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_a82e4782707be8ef551bb2649178efd67"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#a82e4782707be8ef551bb2649178efd67">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::MmaTensorOpMultiplicandTileIterator</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1061</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aae461549926e9f040e3376d709122682"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aae461549926e9f040e3376d709122682">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::load_with_byte_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void load_with_byte_offset(Fragment &amp;frag, Index byte_offset) const </div><div class="ttdoc">Loads a fragment from memory with additional logical offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2590</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_ae84c72fbea0d63d08408fc6bceffe135"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#ae84c72fbea0d63d08408fc6bceffe135">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator(TensorRef const &amp;ref, int lane_id)</div><div class="ttdoc">Constructor from TensorRef. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1899</div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1TensorOpMultiplicandCrosswise.html">cutlass::layout::TensorOpMultiplicandCrosswise</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:632</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a06719b16473c4d23a4db597439199582"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a06719b16473c4d23a4db597439199582">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::Element</a></div><div class="ttdeci">Element_ Element</div><div class="ttdoc">Element type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:116</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_affeae7791be815ff2e0c99c60b079dab"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#affeae7791be815ff2e0c99c60b079dab">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::LongIndex</a></div><div class="ttdeci">typename TensorRef::LongIndex LongIndex</div><div class="ttdoc">Long Index type. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2448</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_aa8b7ca3aa65707a67da0f1e1f9abc6bf"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#aa8b7ca3aa65707a67da0f1e1f9abc6bf">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:629</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a03318bc6554c900c68a6065fad2afbb0"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a03318bc6554c900c68a6065fad2afbb0">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1392</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a0e3aca80cfc279e9e207a3044e925dc9"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a0e3aca80cfc279e9e207a3044e925dc9">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::operator-=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator-=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2250</div></div>
<div class="ttc" id="namespacecutlass_1_1gemm_html_a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6"><div class="ttname"><a href="namespacecutlass_1_1gemm.html#a34338284023da7403c9ecbd3f406b2a6a3e56c011b37f0bc78fb9eb175c1181c6">cutlass::gemm::Operand::kB</a></div><div class="ttdoc">A multiplicand. </div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a4837610efc606b2c8103f8271faad178"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a4837610efc606b2c8103f8271faad178">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:850</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21_html_af02b9089644245ee0d7cd4fab17b2026"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0c7d419c589d601ce4eb603be566fea21.html#af02b9089644245ee0d7cd4fab17b2026">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1202</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a5f71a3fd5d0ee7ecf6ab1278b21e0574"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a5f71a3fd5d0ee7ecf6ab1278b21e0574">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:619</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a8ee105d5111f138a733467935ccfbb63"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a8ee105d5111f138a733467935ccfbb63">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2149</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a081c62bfb91fdf105e97427c58b1bca1"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a081c62bfb91fdf105e97427c58b1bca1">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2182</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_ae44384c7f4d58288c04ac4fabfd86c25"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#ae44384c7f4d58288c04ac4fabfd86c25">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset, Index pointer_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2314</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aa6757114de97d47339a97caa1ff5d863"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aa6757114de97d47339a97caa1ff5d863">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2535</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef_html_a9ce64fa398716ceb18123a34cb8c7eef"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___039819fb3ccd43786d556c2c9669508ef.html#a9ce64fa398716ceb18123a34cb8c7eef">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator--</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator--()</div><div class="ttdoc">Advances the iterator along the advance dimension. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:800</div></div>
<div class="ttc" id="cutlass_8h_html"><div class="ttname"><a href="cutlass_8h.html">cutlass.h</a></div><div class="ttdoc">Basic include for CUTLASS. </div></div>
<div class="ttc" id="structcutlass_1_1MatrixCoord_html"><div class="ttname"><a href="structcutlass_1_1MatrixCoord.html">cutlass::MatrixCoord</a></div><div class="ttdef"><b>Definition:</b> matrix_coord.h:39</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_aaad8afd436ee02d232e37aebdd0e2a8e"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#aaad8afd436ee02d232e37aebdd0e2a8e">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::MmaTensorOpAccumulatorTileIterator</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator()</div><div class="ttdoc">Default ctor constructs null iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2492</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c_html_a1b80f59bc16c01c0a5a347f36080d809"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0ed7daaeba1c095e77f68533d4d2c475c.html#a1b80f59bc16c01c0a5a347f36080d809">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::TensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, 64 &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:144</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a3d83eeb065bda5634f6d739c1584bee0"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a3d83eeb065bda5634f6d739c1584bee0">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::load</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE void load(Fragment &amp;frag) const </div><div class="ttdoc">Loads a fragment from memory at the location pointed to by the iterator. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:592</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b_html_a2b8a09d931c351b3c252ee1a72147208"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0e52ad425e1ee3e68544873f66733237b.html#a2b8a09d931c351b3c252ee1a72147208">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpMultiplicandTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1462</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_afefe082ee98be3a0a7dfdadba702d58f"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#afefe082ee98be3a0a7dfdadba702d58f">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::operator+=</a></div><div class="ttdeci">CUTLASS_DEVICE MmaTensorOpAccumulatorTileIterator &amp; operator+=(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">advances in units of whole tiles along the logical coordinate space of the tensor ...</div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2542</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_abcc77e7414e927a6626f614e5c3067ff"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#abcc77e7414e927a6626f614e5c3067ff">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:501</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98_html_a56f39dc886dc0888713d623687d9ed90"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___006c39f57875e0aa9d0ad82c8043ed8b98.html#a56f39dc886dc0888713d623687d9ed90">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::RowMajor, InstructionShape_, OpDelta_ &gt;::load</a></div><div class="ttdeci">CUTLASS_DEVICE void load(Fragment &amp;frag, TensorCoord const &amp;tile_offset) const </div><div class="ttdoc">Loads a fragment from memory with logical offset in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2006</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_ae8e8ffd03b9d6b239f6406d4278ad9e4"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ae8e8ffd03b9d6b239f6406d4278ad9e4">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::store_with_pointer_offset</a></div><div class="ttdeci">CUTLASS_DEVICE void store_with_pointer_offset(Fragment const &amp;frag, Index pointer_offset) const </div><div class="ttdoc">Stores a fragment to memory with additional pointer offset. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2624</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_ad4d7d684cb7d920211e1c732ad876e55"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#ad4d7d684cb7d920211e1c732ad876e55">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::TensorCoord</a></div><div class="ttdeci">typename TensorRef::TensorCoord TensorCoord</div><div class="ttdoc">Coordinate for an element in the tensor. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2451</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556_html_a9f08f1ae1bfbe2b3fdad0105d5f36cfc"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0352e0dcab42bc8360606874e00173556.html#a9f08f1ae1bfbe2b3fdad0105d5f36cfc">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::RowMajorTensorOpMultiplicandCrosswise&lt; sizeof_bits&lt; Element_ &gt;::value, Crosswise &gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::InstructionShape</a></div><div class="ttdeci">InstructionShape_ InstructionShape</div><div class="ttdoc">Shape of one matrix product operation (concept: MatrixShape) </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:1603</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510_html_a81f5416db0a2add284cbfb6b0c422e94"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___00027dabdc144edd6276f664ca74088510.html#a81f5416db0a2add284cbfb6b0c422e94">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajorInterleaved&lt; InterleavedN &gt;, InstructionShape_, OpDelta_ &gt;::Fragment</a></div><div class="ttdeci">Array&lt; Element, Shape::kCount/kThreads &gt; Fragment</div><div class="ttdoc">Fragment object holding a thread&amp;#39;s part of a tile. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2481</div></div>
<div class="ttc" id="classcutlass_1_1TensorRef_html_adeada5e33b231f125a4aaeaf963bd3a3"><div class="ttname"><a href="classcutlass_1_1TensorRef.html#adeada5e33b231f125a4aaeaf963bd3a3">cutlass::TensorRef::LongIndex</a></div><div class="ttdeci">typename Layout::LongIndex LongIndex</div><div class="ttdoc">Long index used for pointer offsets. </div><div class="ttdef"><b>Definition:</b> tensor_ref.h:168</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c_html_a5b065c7d3bcc3ac6826e65dab9092bd3"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpMultiplicandTileIterator_3_01Shape___00_01Operand___0b84f53cd44b339eccc12067c9f86e11c.html#a5b065c7d3bcc3ac6826e65dab9092bd3">cutlass::gemm::warp::MmaTensorOpMultiplicandTileIterator&lt; Shape_, Operand_, Element_, cutlass::layout::ColumnMajorTensorOpMultiplicandCongruous&lt; sizeof_bits&lt; Element_ &gt;::value, int(128/sizeof(Element_))&gt;, InstructionShape_, OpDelta_, 32, PartitionsK_ &gt;::add_tile_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpMultiplicandTileIterator &amp; add_tile_offset(TensorCoord const &amp;tile_offset)</div><div class="ttdoc">Advances an iterator along logical dimensions of matrix in units of whole tiles. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:551</div></div>
<div class="ttc" id="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCongruous_html"><div class="ttname"><a href="structcutlass_1_1layout_1_1RowMajorTensorOpMultiplicandCongruous.html">cutlass::layout::RowMajorTensorOpMultiplicandCongruous</a></div><div class="ttdef"><b>Definition:</b> tensor_op_multiplicand_sm75.h:527</div></div>
<div class="ttc" id="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042_html_a1bd195c67970a5139c1c4f23e6c5f870"><div class="ttname"><a href="classcutlass_1_1gemm_1_1warp_1_1MmaTensorOpAccumulatorTileIterator_3_01Shape___00_01Element___008f607b871a2b3d854eb4def64712c042.html#a1bd195c67970a5139c1c4f23e6c5f870">cutlass::gemm::warp::MmaTensorOpAccumulatorTileIterator&lt; Shape_, Element_, cutlass::layout::ColumnMajor, InstructionShape_, OpDelta_ &gt;::add_pointer_offset</a></div><div class="ttdeci">CUTLASS_HOST_DEVICE MmaTensorOpAccumulatorTileIterator &amp; add_pointer_offset(LongIndex offset)</div><div class="ttdoc">Adds a pointer offset to internal pointer(s) to advance through memory. </div><div class="ttdef"><b>Definition:</b> mma_tensor_op_tile_iterator.h:2213</div></div>
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